MedWorm.com provides a medical RSS filtering service. Over 6000 RSS medical sources are combined and output via different filters. This feed contains the latest items from the 'Biometrics' source. Mon, 06 Feb 2012 18:10:47 +0100 http://www.medworm.com/index.php?rid=5556849&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01725.x SummaryWe provide methods that can be used to obtain more accurate environmental exposure assessment. In particular, we propose two modeling approaches to combine monitoring data at point level with numerical model output at grid cell level, yielding improved prediction of ambient exposure at point level. Extending our earlier downscaler model (Berrocal, V. J., Gelfand, A. E., and Holland, D. M. (2010b). A spatio‐temporal downscaler for outputs from numerical models. Journal of Agricultural, Biological and Environmental Statistics15, 176–197), these new models are intended to address two potential concerns with the model output. One recognizes that there may be useful information in the outputs for grid cells that are neighbors of the one in which the location lies. The second acknowle... Biometrics journals http://www.medworm.com/rss/comments.php?id=5556849 Thu, 29 Dec 2011 05:00:00 +0100 5556849 http://www.medworm.com/index.php?rid=5512485&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01721.x SummaryTemporal boundary misalignment occurs when area boundaries shift across time (e.g., census tract boundaries change at each census year), complicating the modeling of temporal trends across space. Large area‐level datasets with temporal boundary misalignment are becoming increasingly common in practice. The few existing approaches for temporally misaligned data do not account for correlation in spatial random effects over time. To overcome issues associated with temporal misalignment, we construct a geostatistical model for aggregate count data by assuming that an underlying continuous risk surface induces spatial correlation between areas. We implement the model within the framework of a generalized linear mixed model using radial basis splines. Using this approach, boundary misal... Biometrics journals http://www.medworm.com/rss/comments.php?id=5512485 Fri, 16 Dec 2011 05:00:00 +0100 5512485 http://www.medworm.com/index.php?rid=5512486&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01715.x Summary In some survival analysis of medical studies, there are often long‐term survivors who can be considered as permanently cured. The goals in these studies are to estimate the noncured probability of the whole population and the hazard rate of the susceptible subpopulation. When covariates are present as often happens in practice, to understand covariate effects on the noncured probability and hazard rate is of equal importance. The existing methods are limited to parametric and semiparametric models. We propose a two‐component mixture cure rate model with nonparametric forms for both the cure probability and the hazard rate function. Identifiability of the model is guaranteed by an additive assumption that allows no time–covariate interactions in the logarithm of hazard rate. E... Biometrics journals http://www.medworm.com/rss/comments.php?id=5512486 Wed, 14 Dec 2011 05:00:00 +0100 5512486 http://www.medworm.com/index.php?rid=5483441&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01719.x Summary It is a common practice to analyze complex longitudinal data using semiparametric nonlinear mixed‐effects (SNLME) models with a normal distribution. Normality assumption of model errors may unrealistically obscure important features of subject variations. To partially explain between‐ and within‐subject variations, covariates are usually introduced in such models, but some covariates may often be measured with substantial errors. Moreover, the responses may be missing and the missingness may be nonignorable. Inferential procedures can be complicated dramatically when data with skewness, missing values, and measurement error are observed. In the literature, there has been considerable interest in accommodating either skewness, incompleteness or covariate measurement error in s... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483441 Wed, 07 Dec 2011 05:00:00 +0100 5483441 http://www.medworm.com/index.php?rid=5483440&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01712.x Summary The current statistical literature on causal inference is primarily concerned with population means of potential outcomes, while the current statistical practice also involves other meaningful quantities such as quantiles. Motivated by the Consortium on Safe Labor (CSL), a large observational study of obstetric labor progression, we propose and compare methods for estimating marginal quantiles of potential outcomes as well as quantiles among the treated. By adapting existing methods and techniques, we derive estimators based on outcome regression (OR), inverse probability weighting, and stratification, as well as a doubly robust (DR) estimator. By incorporating stratification into the DR estimator, we further develop a hybrid estimator with enhanced numerical stability at the expen... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483440 Wed, 07 Dec 2011 05:00:00 +0100 5483440 http://www.medworm.com/index.php?rid=5483439&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01720.x Summary Phase II trials in oncology are usually conducted as single‐arm two‐stage designs with binary endpoints. Currently available adaptive design methods are tailored to comparative studies with continuous test statistics. Direct transfer of these methods to discrete test statistics results in conservative procedures and, therefore, in a loss in power. We propose a method based on the conditional error function principle that directly accounts for the discreteness of the outcome. It is shown how application of the method can be used to construct new phase II designs that are more efficient as compared to currently applied designs and that allow flexible mid‐course design modifications. The proposed method is illustrated with a variety of frequently used phase II designs. (Source: ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483439 Wed, 07 Dec 2011 05:00:00 +0100 5483439 http://www.medworm.com/index.php?rid=5483438&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01713.x Summary Case–parent trio studies concerned with children affected by a disease and their parents aim to detect single nucleotide polymorphisms (SNPs) showing a preferential transmission of alleles from the parents to their affected offspring. A popular statistical test for detecting such SNPs associated with disease in this study design is the genotypic transmission/disequilibrium test (gTDT) based on a conditional logistic regression model, which usually needs to be fitted by an iterative procedure. In this article, we derive exact closed‐form solutions for the parameter estimates of the conditional logistic regression models when testing for an additive, a dominant, or a recessive effect of a SNP, and show that such analytic parameter estimates also exist when considering gene–envi... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483438 Wed, 07 Dec 2011 05:00:00 +0100 5483438 http://www.medworm.com/index.php?rid=5483437&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01671.x SummaryTo develop more targeted intervention strategies, an important research goal is to identify markers predictive of clinical events. A crucial step toward this goal is to characterize the clinical performance of a marker for predicting different types of events. In this article, we present statistical methods for evaluating the performance of a prognostic marker in predicting multiple competing events. To capture the potential time‐varying predictive performance of the marker and incorporate competing risks, we define time‐ and cause‐specific accuracy summaries by stratifying cases based on causes of failure. Such definition would allow one to evaluate the predictive accuracy of a marker for each type of event and compare its predictiveness across event types. Extending the nonp... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483437 Wed, 07 Dec 2011 05:00:00 +0100 5483437 http://www.medworm.com/index.php?rid=5483436&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01716.x SummaryWe establish a connection between a class of chain‐binomial models of use in ecology and epidemiology and binomial autoregressive (AR) processes. New results are obtained for the latter, including expressions for the lag‐ conditional distribution and related quantities. We focus on two types of chain‐binomial model, extinction–colonization and colonization–extinction models, and present two approaches to parameter estimation. The asymptotic distributions of the resulting estimators are studied, as well as their finite‐sample performance, and we give an application to real data. A connection is made with standard AR models, which also has implications for parameter estimation. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5483436 Wed, 07 Dec 2011 05:00:00 +0100 5483436 http://www.medworm.com/index.php?rid=5656646&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01722.x Summary Treatment‐selection markers are biological molecules or patient characteristics associated with one’s response to treatment. They can be used to predict treatment effects for individual subjects and subsequently help deliver treatment to those most likely to benefit from it. Statistical tools are needed to evaluate a marker’s capacity to help with treatment selection. The commonly adopted criterion for a good treatment‐selection marker has been the interaction between marker and treatment. While a strong interaction is important, it is, however, not sufficient for good marker performance. In this article, we develop novel measures for assessing a continuous treatment‐selection marker, based on a potential outcomes framework. Under a set of assumptions, we derive the optim... Biometrics journals http://www.medworm.com/rss/comments.php?id=5656646 Thu, 01 Dec 2011 05:00:00 +0100 5656646 http://www.medworm.com/index.php?rid=5635588&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01709.x Summary Knowing which populations are most at risk for severe outcomes from an emerging infectious disease is crucial in deciding the optimal allocation of resources during an outbreak response. The case fatality ratio (CFR) is the fraction of cases that die after contracting a disease. The relative CFR is the factor by which the case fatality in one group is greater or less than that in a second group. Incomplete reporting of the number of infected individuals, both recovered and dead, can lead to biased estimates of the CFR. We define conditions under which the CFR and the relative CFR are identifiable. Furthermore, we propose an estimator for the relative CFR that controls for time‐varying reporting rates. We generalize our methods to account for elapsed time between infection and dea... Biometrics journals http://www.medworm.com/rss/comments.php?id=5635588 Thu, 01 Dec 2011 05:00:00 +0100 5635588 http://www.medworm.com/index.php?rid=5617167&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01730.x This article aims to introduce a robust testing and probe ranking procedure based on a nonhomogeneous hidden Markov model that incorporates the above‐mentioned features for detecting differential methylation. We revisit the seminal work of Sun and Cai (2009, Journal of the Royal Statistical Society: Series B (Statistical Methodology)71, 393–424) and propose modeling the nonnull using a nonparametric symmetric distribution in two‐sided hypothesis testing. We show that this model improves probe ranking and is robust to model misspecification based on extensive simulation studies. We further illustrate that our proposed framework achieves good operating characteristics as compared to commonly used methods in real DNA methylation data that aims to detect differential methylation sites. (... Biometrics journals http://www.medworm.com/rss/comments.php?id=5617167 Thu, 01 Dec 2011 05:00:00 +0100 5617167 http://www.medworm.com/index.php?rid=5569045&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01724.x SummaryUsing a new type of array technology, the reverse phase protein array (RPPA), we measure time‐course protein expression for a set of selected markers that are known to coregulate biological functions in a pathway structure. To accommodate the complex dependent nature of the data, including temporal correlation and pathway dependence for the protein markers, we propose a mixed effects model with temporal and protein‐specific components. We develop a sequence of random probability measures (RPM) to account for the dependence in time of the protein expression measurements. Marginally, for each RPM we assume a Dirichlet process model. The dependence is introduced by defining multivariate beta distributions for the unnormalized weights of the stick‐breaking representation. We also ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5569045 Thu, 01 Dec 2011 05:00:00 +0100 5569045 http://www.medworm.com/index.php?rid=5556848&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01726.x SummaryArray‐based group‐testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in array testing to account for heterogeneity among individuals being tested. We first derive closed‐form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two‐dimensional array testing in a heterogeneous population. We then propose two “informative” array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct o... Biometrics journals http://www.medworm.com/rss/comments.php?id=5556848 Thu, 01 Dec 2011 05:00:00 +0100 5556848 http://www.medworm.com/index.php?rid=5549886&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01723.x Summary The median failure time is often utilized to summarize survival data because it has a more straightforward interpretation for investigators in practice than the popular hazard function. However, existing methods for comparing median failure times for censored survival data either require estimation of the probability density function or involve complicated formulas to calculate the variance of the estimates. In this article, we modify a K‐sample median test for censored survival data (Brookmeyer and Crowley, 1982, Journal of the American Statistical Association77, 433–440) through a simple contingency table approach where each cell counts the number of observations in each sample that are greater than the pooled median or vice versa. Under censoring, this approach would generat... Biometrics journals http://www.medworm.com/rss/comments.php?id=5549886 Thu, 01 Dec 2011 05:00:00 +0100 5549886 http://www.medworm.com/index.php?rid=5512495&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01707.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512495 Thu, 01 Dec 2011 05:00:00 +0100 5512495 http://www.medworm.com/index.php?rid=5512494&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01706.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512494 Thu, 01 Dec 2011 05:00:00 +0100 5512494 http://www.medworm.com/index.php?rid=5512493&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01705.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512493 Thu, 01 Dec 2011 05:00:00 +0100 5512493 http://www.medworm.com/index.php?rid=5512492&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01704.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512492 Thu, 01 Dec 2011 05:00:00 +0100 5512492 http://www.medworm.com/index.php?rid=5512491&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01703.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512491 Thu, 01 Dec 2011 05:00:00 +0100 5512491 http://www.medworm.com/index.php?rid=5512490&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01702.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512490 Thu, 01 Dec 2011 05:00:00 +0100 5512490 http://www.medworm.com/index.php?rid=5512489&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01701.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512489 Thu, 01 Dec 2011 05:00:00 +0100 5512489 http://www.medworm.com/index.php?rid=5512488&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01700.x Statistics in Human Genetics and Molecular Biology(C. Reilly)              Xiang‐Yang Lou and David B. AllisonMeta‐Analysis and Combining Information in Genetics and Genomics(R. Guerra and D. R. Goldstein)              Peter H. WestfallMultivariate Nonparametric Methods with R. An Approach Based on Spatial Signs and Ranks(H. Oja)              Mia HubertBayesian Analysis for Population Ecology(R. King, B. J. T. Morgan, O. Gimenez, and S. Brooks)              Simon BonnerThe Oxford Handbook of Functional Data Analysis(F. Ferraty and Y. Romain, Editors)              Paul H. C. EilersDesign and Analysis of Experiments with SAS(J. Lawson)     ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5512488 Thu, 01 Dec 2011 05:00:00 +0100 5512488 http://www.medworm.com/index.php?rid=5512487&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01698.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512487 Thu, 01 Dec 2011 05:00:00 +0100 5512487 http://www.medworm.com/index.php?rid=5512484&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01717.x SummaryLinking information on a movement network with space–time data on disease incidence is one of the key challenges in infectious disease epidemiology. In this article, we propose and compare two statistical frameworks for this purpose, namely, parameter‐driven (PD) and observation‐driven (OD) models. Bayesian inference in PD models is done using integrated nested Laplace approximations, while OD models can be easily fitted with existing software using maximum likelihood. The predictive performance of both formulations is assessed using proper scoring rules. As a case study, the impact of cattle trade on the spatiotemporal spread of Coxiellosis in Swiss cows, 2004–2009, is finally investigated. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5512484 Thu, 01 Dec 2011 05:00:00 +0100 5512484 http://www.medworm.com/index.php?rid=5417775&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01698.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5417775 Mon, 14 Nov 2011 05:00:00 +0100 5417775 http://www.medworm.com/index.php?rid=5396939&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01682.x Summary Biomarkers play an increasing role in the clinical development of new therapeutics. Earlier clinical decisions facilitated by biomarkers can lead to reduced costs and duration of drug development. Associations between biomarkers and clinical endpoints are often viewed as initial evidence supporting the intended purpose. As a result, even though it is widely understood that correlation is not proof of a causal relationship, correlation continues to be used as a metric for biomarker qualification in practice. In this article, we introduce a causal correlation framework where two different types of correlations are defined at the individual level. We show that the correlation estimate is a composite of different components, and needs to be interpreted with caution when used for biomar... Biometrics journals http://www.medworm.com/rss/comments.php?id=5396939 Mon, 07 Nov 2011 05:00:00 +0100 5396939 http://www.medworm.com/index.php?rid=5396938&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01696.x Summary In medical studies, it is often of scientific interest to evaluate the treatment effect via the ratio of cumulative hazards, especially when those hazards may be nonproportional. To deal with nonproportionality in the Cox regression model, investigators usually assume that the treatment effect has some functional form. However, to do so may create a model misspecification problem because it is generally difficult to justify the specific parametric form chosen for the treatment effect. In this article, we employ empirical likelihood (EL) to develop a nonparametric estimator of the cumulative hazard ratio with covariate adjustment under two nonproportional hazard models, one that is stratified, as well as a less restrictive framework involving group‐specific treatment adjustment. T... Biometrics journals http://www.medworm.com/rss/comments.php?id=5396938 Mon, 07 Nov 2011 05:00:00 +0100 5396938 http://www.medworm.com/index.php?rid=5396937&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01697.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5396937 Mon, 07 Nov 2011 05:00:00 +0100 5396937 http://www.medworm.com/index.php?rid=5375727&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01703.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5375727 Thu, 03 Nov 2011 04:00:00 +0100 5375727 http://www.medworm.com/index.php?rid=5375726&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01670.x Summary.  After more than 60 years, the Legislative Council overwhelming approved a revised governance structure for the International Biometric Society (IBS) to take effect from 1 January 2012. Responsibility for the governance and leadership of the society will be combined and placed in the hands of an Executive Board, supported by a much larger Representative Council. The Representative Council will be composed of members selected by the different regions (or geographical components) of the society. It will be responsible for overseeing the nomination and election (by the whole society) of the Executive Board and provide the conduit between the regions and this leadership team. Members of the Representative Council will also chair the Standing Committees. The transition process to the... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375726 Thu, 03 Nov 2011 04:00:00 +0100 5375726 http://www.medworm.com/index.php?rid=5375725&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01668.x This article proposes methodology for assessing goodness of fit in Bayesian hierarchical models. The methodology is based on comparing values of pivotal discrepancy measures (PDMs), computed using parameter values drawn from the posterior distribution, to known reference distributions. Because the resulting diagnostics can be calculated from standard output of Markov chain Monte Carlo algorithms, their computational costs are minimal. Several simulation studies are provided, each of which suggests that diagnostics based on PDMs have higher statistical power than comparable posterior‐predictive diagnostic checks in detecting model departures. The proposed methodology is illustrated in a clinical application; an application to discrete data is described in supplementary material. (Source: ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375725 Thu, 03 Nov 2011 04:00:00 +0100 5375725 http://www.medworm.com/index.php?rid=5375724&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01666.x Summary Two approaches commonly used to deal with missing data are multiple imputation (MI) and inverse‐probability weighting (IPW). IPW is also used to adjust for unequal sampling fractions. MI is generally more efficient than IPW but more complex. Whereas IPW requires only a model for the probability that an individual has complete data (a univariate outcome), MI needs a model for the joint distribution of the missing data (a multivariate outcome) given the observed data. Inadequacies in either model may lead to important bias if large amounts of data are missing. A third approach combines MI and IPW to give a doubly robust estimator. A fourth approach (IPW/MI) combines MI and IPW but, unlike doubly robust methods, imputes only isolated missing values and uses weights to account for re... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375724 Thu, 03 Nov 2011 04:00:00 +0100 5375724 http://www.medworm.com/index.php?rid=5375723&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01665.x Summary Nonlinear mixed effects models allow investigating individual differences in drug concentration profiles (pharmacokinetics) and responses. Pharmacogenetics focuses on the genetic component of this variability. Two tests often used to detect a gene effect on a pharmacokinetic parameter are (1) the Wald test, assessing whether estimates for the gene effect are significantly different from 0 and (2) the likelihood ratio test comparing models with and without the genetic effect. Because those asymptotic tests show inflated type I error on small sample size and/or with unevenly distributed genotypes, we develop two alternatives and evaluate them by means of a simulation study. First, we assess the performance of the permutation test using the Wald and the likelihood ratio statistics. Se... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375723 Thu, 03 Nov 2011 04:00:00 +0100 5375723 http://www.medworm.com/index.php?rid=5375729&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01699.x Summary A simple method to select a spatially balanced sample using equal or unequal inclusion probabilities is presented. For populations with spatial trends in the variables of interest, the estimation can be much improved by selecting samples that are well spread over the population. The method can be used for any number of dimensions and can hence also select spatially balanced samples in a space spanned by several auxiliary variables. Analysis and examples indicate that the suggested method achieves a high degree of spatial balance and is therefore efficient for populations with trends. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5375729 Mon, 31 Oct 2011 04:00:00 +0100 5375729 http://www.medworm.com/index.php?rid=5375728&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01693.x The objective is to estimate the success probability of an experimental therapy for each subtype. We consider the case when small sample sizes require extensive borrowing of information across subtypes, but the subtypes are not a priori exchangeable. The lack of a priori exchangeability hinders the straightforward use of traditional hierarchical models to implement borrowing of strength across disease subtypes. We introduce instead a random partition model for the set of disease subtypes. This is a variation of the product partition model that allows us to model a nonexchangeable prior structure. Like a hierarchical model, the proposed clustering approach considers all observations, across all disease subtypes, to estimate individual success probabilities. But in contrast to standard hiera... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375728 Mon, 31 Oct 2011 04:00:00 +0100 5375728 http://www.medworm.com/index.php?rid=5330920&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01695.x Summary Genetic imprinting and in utero maternal effects are causes of parent‐of‐origin effect but they are confounded with each other. Tests attempting to detect only one of these effects would have a severely inflated type I error rate if the assumption of the absence of the other effect is violated. Some existing methods avoid the potential confounding by modeling imprinting and in utero maternal effect simultaneously. However, these methods are not amendable to extended families, which are commonly recruited in family‐based studies. In this article, we propose a likelihood approach for detecting imprinting and maternal effects (LIME) using general pedigrees from prospective family‐based association studies. LIME formulates the probability of familial genotypes without the Hardy... Biometrics journals http://www.medworm.com/rss/comments.php?id=5330920 Tue, 18 Oct 2011 04:00:00 +0100 5330920 http://www.medworm.com/index.php?rid=5330923&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01688.x Summary A common goal of microarray and related high‐throughput genomic experiments is to identify genes that vary across biological condition. Most often this is accomplished by identifying genes with changes in mean expression level, so called differentially expressed (DE) genes, and a number of effective methods for identifying DE genes have been developed. Although useful, these approaches do not accommodate other types of differential regulation. An important example concerns differential coexpression (DC). Investigations of this class of genes are hampered by the large cardinality of the space to be interrogated as well as by influential outliers. As a result, existing DC approaches are often underpowered, exceedingly prone to false discoveries, and/or computationally intractable f... Biometrics journals http://www.medworm.com/rss/comments.php?id=5330923 Mon, 17 Oct 2011 04:00:00 +0100 5330923 http://www.medworm.com/index.php?rid=5330922&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01690.x Summary Uncertainty concerning the measurement error properties of self‐reported diet has important implications for the reliability of nutritional epidemiology reports. Biomarkers based on the urinary recovery of expended nutrients can provide an objective measure of short‐term nutrient consumption for certain nutrients and, when applied to a subset of a study cohort, can be used to calibrate corresponding self‐report nutrient consumption assessments. A nonstandard measurement error model that makes provision for systematic error and subject‐specific error, along with the usual independent random error, is needed for the self‐report data. Three estimation procedures for hazard ratio (Cox model) parameters are extended for application to this more complex measurement error struct... Biometrics journals http://www.medworm.com/rss/comments.php?id=5330922 Mon, 17 Oct 2011 04:00:00 +0100 5330922 http://www.medworm.com/index.php?rid=5330921&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01687.x Summary For many diseases the infection status of individuals cannot be observed directly, but can only be inferred from biomarkers that are subject to measurement error. Diagnosis of infection based on observed symptoms can itself be regarded as an imperfect test of infection status. The temporal relationship between infection and marker outcomes may be complex, especially for recurrent diseases where individuals can experience multiple bouts of infection. We propose an approach that first models the unobserved longitudinal infection status of individuals conditional on relevant covariates, and then jointly models the longitudinal sequence of biomarker outcomes conditional on infection status and covariate information through time, thus resulting in a joint model for longitudinal infectio... Biometrics journals http://www.medworm.com/rss/comments.php?id=5330921 Mon, 17 Oct 2011 04:00:00 +0100 5330921 http://www.medworm.com/index.php?rid=5301913&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01684.x Summary A novel point process model continuous in space–time is proposed for quantifying the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002–2008. Modeling is based on the conditional intensity function (CIF), which is described by a superposition of additive and multiplicative components. As an epidemiological interesting finding, spread behavior was shown to depend on type in addition to age: basic reproduction numbers were 0.25 (95% CI 0.19–0.34) and 0.11 (95% CI 0.07–0.17) for types B:P1.7–2,4:F1–5 and C:P1.5,2:F3–3, respectively. Altogether, the proposed methodology represents a comprehensive and universal regression framework for the modeling, simulation, and inference of self‐exciting spatiotemporal point p... Biometrics journals http://www.medworm.com/rss/comments.php?id=5301913 Sun, 09 Oct 2011 04:00:00 +0100 5301913 http://www.medworm.com/index.php?rid=5268776&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01677.x Summary Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene–environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain pow... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268776 Wed, 28 Sep 2011 04:00:00 +0100 5268776 http://www.medworm.com/index.php?rid=5268775&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01678.x Summary We consider the penalized generalized estimating equations (GEEs) for analyzing longitudinal data with high‐dimensional covariates, which often arise in microarray experiments and large‐scale health studies. Existing high‐dimensional regression procedures often assume independent data and rely on the likelihood function. Construction of a feasible joint likelihood function for high‐dimensional longitudinal data is challenging, particularly for correlated discrete outcome data. The penalized GEE procedure only requires specifying the first two marginal moments and a working correlation structure. We establish the asymptotic theory in a high‐dimensional framework where the number of covariates pn increases as the number of clusters n increases, and pn can reach ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268775 Wed, 28 Sep 2011 04:00:00 +0100 5268775 http://www.medworm.com/index.php?rid=5268774&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01679.x Summary Recent guidance from the Food and Drug Administration for the evaluation of new therapies in the treatment of type 2 diabetes (T2DM) calls for a program‐wide meta‐analysis of cardiovascular (CV) outcomes. In this context, we develop a new Bayesian meta‐analysis approach using survival regression models to assess whether the size of a clinical development program is adequate to evaluate a particular safety endpoint. We propose a Bayesian sample size determination methodology for meta‐analysis clinical trial design with a focus on controlling the type I error and power. We also propose the partial borrowing power prior to incorporate the historical survival meta data into the statistical design. Various properties of the proposed methodology are examined and an efficient ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268774 Wed, 28 Sep 2011 04:00:00 +0100 5268774 http://www.medworm.com/index.php?rid=5268773&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01680.x Summary Rare variants have been heralded as key to uncovering “missing heritability” in complex diseases. These variants can now be genotyped using next‐generation sequencing technologies; nonetheless, rare haplotypes may also result from combination of common single nucleotide polymorphisms available from genome‐wide association studies (GWAS). The National Eye Institute’s data on age‐related macular degeneration (AMD) is such an example. Studies on AMD had identified potential rare variants; however, due to lack of appropriate statistical tools, effects of individual rare haplotypes were never studied. Here we develop a method for identifying association with rare haplotypes for case–control design. A logistic regression based retrospective likelihood is formulated and is r... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268773 Wed, 28 Sep 2011 04:00:00 +0100 5268773 http://www.medworm.com/index.php?rid=5268779&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01667.x Summary Double censoring often occurs in registry studies when left censoring is present in addition to right censoring. In this work, we propose a new analysis strategy for such doubly censored data by adopting a quantile regression model. We develop computationally simple estimation and inference procedures by appropriately using the embedded martingale structure. Asymptotic properties, including the uniform consistency and weak convergence, are established for the resulting estimators. Moreover, we propose conditional inference to address the special identifiability issues attached to the double censoring setting. We further show that the proposed method can be readily adapted to handle left truncation. Simulation studies demonstrate good finite‐sample performance of the new inferenti... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268779 Tue, 27 Sep 2011 04:00:00 +0100 5268779 http://www.medworm.com/index.php?rid=5268778&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01674.x This article examines group testing procedures where units within a group (or pool) may be correlated. The expected number of tests per unit (i.e., efficiency) of hierarchical‐ and matrix‐based procedures is derived based on a class of models of exchangeable binary random variables. The effect on efficiency of the arrangement of correlated units within pools is then examined. In general, when correlated units are arranged in the same pool, the expected number of tests per unit decreases, sometimes substantially, relative to arrangements that ignore information about correlation. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5268778 Tue, 27 Sep 2011 04:00:00 +0100 5268778 http://www.medworm.com/index.php?rid=5268777&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01675.x Summary Inference regarding the inclusion or exclusion of random effects in linear mixed models is challenging because the variance components are located on the boundary of their parameter space under the usual null hypothesis. As a result, the asymptotic null distribution of the Wald, score, and likelihood ratio tests will not have the typical χ2 distribution. Although it has been proved that the correct asymptotic distribution is a mixture of χ2 distributions, the appropriate mixture distribution is rather cumbersome and nonintuitive when the null and alternative hypotheses differ by more than one random effect. As alternatives, we present two permutation tests, one that is based on the best linear unbiased predictors and one that is based on the restricted likelihood ratio test stati... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268777 Tue, 27 Sep 2011 04:00:00 +0100 5268777 http://www.medworm.com/index.php?rid=5257354&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01672.x Summary The additive model is a semiparametric class of models that has become extremely popular because it is more flexible than the linear model and can be fitted to high‐dimensional data when fully nonparametric models become infeasible. We consider the problem of simultaneous variable selection and parametric component identification using spline approximation aided by two smoothly clipped absolute deviation (SCAD) penalties. The advantage of our approach is that one can automatically choose between additive models, partially linear additive models and linear models, in a single estimation step. Simulation studies are used to illustrate our method, and we also present its applications to motif regression. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5257354 Fri, 23 Sep 2011 04:00:00 +0100 5257354 http://www.medworm.com/index.php?rid=5483435&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01718.x Summary.  We consider the linear regression of outcome Y on regressors W and Z with some values of W missing, when our main interest is the effect of Z on Y, controlling for W. Three common approaches to regression with missing covariates are (i) complete‐case analysis (CC), which discards the incomplete cases, and (ii) ignorable likelihood methods, which base inference on the likelihood based on the observed data, assuming the missing data are missing at random (Rubin, 1976b), and (iii) nonignorable modeling, which posits a joint distribution of the variables and missing data indicators. Another simple practical approach that has not received much theoretical attention is to drop the regressor variables containing missing values from the regression modeling (DV... Biometrics journals http://www.medworm.com/rss/comments.php?id=5483435 Thu, 01 Sep 2011 04:00:00 +0100 5483435 http://www.medworm.com/index.php?rid=5447749&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01710.x We describe an intuitive strategy for modeling such aggregated, ordered categorical data allowing for inference regarding the category probabilities and a measure of central tendency on the original scale of the data (e.g., meters), along with incorporation of temporal correlation and overdispersion. The strategy extends covariate‐specific cutpoint models for ordinal data. We demonstrate the method in an analysis of SDR dive‐depth data collected on harbor seals in Alaska. The primary goal of the analysis is to assess the relationship of covariates, such as time of day, with number of dives and maximum depth of dives. We also predict missing values and introduce novel graphical summaries of the data and results. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5447749 Thu, 01 Sep 2011 04:00:00 +0100 5447749 http://www.medworm.com/index.php?rid=5417774&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01681.x SummaryThe need to consider in capture‐recapture models random effects besides fixed effects such as those of environmental covariates has been widely recognized over the last years. However, formal approaches require involved likelihood integrations, and conceptual and technical difficulties have slowed down the spread of capture–recapture mixed models among biologists. In this article, we evaluate simple procedures to test for the effect of an environmental covariate on parameters such as time‐varying survival probabilities in presence of a random effect corresponding to unexplained environmental variation. We show that the usual likelihood ratio test between fixed models is strongly biased, and tends to detect too often a covariate effect. Permutation and analysis of deviance test... Biometrics journals http://www.medworm.com/rss/comments.php?id=5417774 Thu, 01 Sep 2011 04:00:00 +0100 5417774 http://www.medworm.com/index.php?rid=5396936&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01683.x Summary. We consider frailty models with additive semiparametric covariate effects for clustered failure time data. We propose a doubly penalized partial likelihood (DPPL) procedure to estimate the nonparametric functions using smoothing splines. We show that the DPPL estimators could be obtained from fitting an augmented working frailty model with parametric covariate effects, whereas the nonparametric functions being estimated as linear combinations of fixed and random effects, and the smoothing parameters being estimated as extra variance components. This approach allows us to conveniently estimate all model components within a unified frailty model framework. We evaluate the finite sample performance of the proposed method via a simulation study, and apply the method to analyze data ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5396936 Thu, 01 Sep 2011 04:00:00 +0100 5396936 http://www.medworm.com/index.php?rid=5375722&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01669.x Summary We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t‐copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy‐tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies... Biometrics journals http://www.medworm.com/rss/comments.php?id=5375722 Thu, 01 Sep 2011 04:00:00 +0100 5375722 http://www.medworm.com/index.php?rid=5343620&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01694.x Summary Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. The error rates according to the latent class model differ from the true error rates, however, and empirical comparisons with a gold standard suggest the true error rates often are larger. We investigate conditions under which the true type I and type II error rates are larger than those provided by the latent class models. Results from Uebersax (1988, Psychological Bulletin 104, 405–41... Biometrics journals http://www.medworm.com/rss/comments.php?id=5343620 Thu, 01 Sep 2011 04:00:00 +0100 5343620 http://www.medworm.com/index.php?rid=5330919&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01691.x Summary In multivariate matching, fine balance constrains the marginal distributions of a nominal variable in treated and matched control groups to be identical without constraining who is matched to whom. In this way, a fine balance constraint can balance a nominal variable with many levels while focusing efforts on other more important variables when pairing individuals to minimize the total covariate distance within pairs. Fine balance is not always possible; that is, it is a constraint on an optimization problem, but the constraint is not always feasible. We propose a new algorithm that returns a minimum distance finely balanced match when one is feasible, and otherwise minimizes the total distance among all matched samples that minimize the deviation from fine balance. Perhaps we can ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5330919 Thu, 01 Sep 2011 04:00:00 +0100 5330919 http://www.medworm.com/index.php?rid=5310917&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01689.x Summary Line transect sampling is one of the most widely used methods for estimating the size of wild animal populations. An assumption in standard line transect sampling is that all the animals on the trackline are detected without fail. This assumption tends to be violated for marine mammals with surfacing/diving behaviors. The detection probability on the trackline is estimated using duplicate sightings from double‐platform line transect methods. The double‐platform methods, however, are insufficient to estimate the abundance of long‐diving animals because these animals can be completely missed while the observers pass. We developed a more flexible hazard probability model that incorporates information on surfacing/diving patterns obtained from telemetry data. The model is based o... Biometrics journals http://www.medworm.com/rss/comments.php?id=5310917 Thu, 01 Sep 2011 04:00:00 +0100 5310917 http://www.medworm.com/index.php?rid=5301912&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01673.x Summary Due to the rising cost of laboratory assays, it has become increasingly common in epidemiological studies to pool biospecimens. This is particularly true in longitudinal studies, where the cost of performing multiple assays over time can be prohibitive. In this article, we consider the problem of estimating the parameters of a Gaussian random effects model when the repeated outcome is subject to pooling. We consider different pooling designs for the efficient maximum likelihood estimation of variance components, with particular attention to estimating the intraclass correlation coefficient. We evaluate the efficiencies of different pooling design strategies using analytic and simulation study results. We examine the robustness of the designs to skewed distributions and consider unb... Biometrics journals http://www.medworm.com/rss/comments.php?id=5301912 Thu, 01 Sep 2011 04:00:00 +0100 5301912 http://www.medworm.com/index.php?rid=5293101&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01685.x Summary Estimating the causal effect of an intervention on a population typically involves defining parameters in a nonparametric structural equation model (Pearl, 2000, Causality: Models, Reasoning, and Inference) in which the treatment or exposure is deterministically assigned in a static or dynamic way. We define a new causal parameter that takes into account the fact that intervention policies can result in stochastically assigned exposures. The statistical parameter that identifies the causal parameter of interest is established. Inverse probability of treatment weighting (IPTW), augmented IPTW (A‐IPTW), and targeted maximum likelihood estimators (TMLE) are developed. A simulation study is performed to demonstrate the properties of these estimators, which include the double robustne... Biometrics journals http://www.medworm.com/rss/comments.php?id=5293101 Thu, 01 Sep 2011 04:00:00 +0100 5293101 http://www.medworm.com/index.php?rid=5268763&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01676.x Summary Large observational databases derived from disease registries and retrospective cohort studies have proven very useful for the study of health services utilization. However, the use of large databases may introduce computational difficulties, particularly when the event of interest is recurrent. In such settings, grouping the recurrent event data into prespecified intervals leads to a flexible event rate model and a data reduction that remedies the computational issues. We propose a possibly stratified marginal proportional rates model with a piecewise‐constant baseline event rate for recurrent event data. Both the absence and the presence of a terminal event are considered. Large‐sample distributions are derived for the proposed estimators. Simulation studies are conducted und... Biometrics journals http://www.medworm.com/rss/comments.php?id=5268763 Thu, 01 Sep 2011 04:00:00 +0100 5268763 http://www.medworm.com/index.php?rid=5257353&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01656.x Summary In principle, G‐estimation is an attractive approach for dealing with confounding by variables affected by treatment. It has rarely been applied for estimation of the effects of treatment on failure‐time outcomes. Part of this is due to artificial censoring, an analytic device which considers some subjects who actually were observed to fail as if they were censored. Artificial censoring leads to a lack of smoothness in the estimating function, which can pose problems in variance estimation and in optimization. It also can lead to failure to have solutions to the usual estimating functions, which then raises questions about the appropriate criteria for optimization. To improve performance of the optimization procedures, we consider approaches for reducing the amount of artificia... Biometrics journals http://www.medworm.com/rss/comments.php?id=5257353 Thu, 01 Sep 2011 04:00:00 +0100 5257353 http://www.medworm.com/index.php?rid=5233617&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_10.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233617 Thu, 01 Sep 2011 04:00:00 +0100 5233617 http://www.medworm.com/index.php?rid=5233616&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_9.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233616 Thu, 01 Sep 2011 04:00:00 +0100 5233616 http://www.medworm.com/index.php?rid=5233615&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_8.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233615 Thu, 01 Sep 2011 04:00:00 +0100 5233615 http://www.medworm.com/index.php?rid=5233614&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_7.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233614 Thu, 01 Sep 2011 04:00:00 +0100 5233614 http://www.medworm.com/index.php?rid=5233613&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_6.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233613 Thu, 01 Sep 2011 04:00:00 +0100 5233613 http://www.medworm.com/index.php?rid=5233612&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_5.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233612 Thu, 01 Sep 2011 04:00:00 +0100 5233612 http://www.medworm.com/index.php?rid=5233611&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_4.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233611 Thu, 01 Sep 2011 04:00:00 +0100 5233611 http://www.medworm.com/index.php?rid=5233610&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_3.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233610 Thu, 01 Sep 2011 04:00:00 +0100 5233610 http://www.medworm.com/index.php?rid=5233609&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_2.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5233609 Thu, 01 Sep 2011 04:00:00 +0100 5233609 http://www.medworm.com/index.php?rid=5233608&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01658_1.x Graphics for Statistics and Data Analysis with R(K. J. Keen)               Michael FriendlyHidden Markov Models for Time Series: An Introduction Using R(W. Zucchini and I. L. MacDonald)               Peter GuttorpBayesian Adaptive Methods for Clinical Trials(S. M. Berry, B. P. Carlin, J. J. Lee, J. J. and P. Muller)          Say Beng TanSAS and R Data Management, Statistical Analysis, and Graphics(K. Kleinman and N. Horton)               Juan P. SteibelNumerical Analysis for Statisticians, 2nd edition(K. Lange)                Maria RizzoStatistical Methods for Disease Clustering(T. Tango)                Lance A. Waller... Biometrics journals http://www.medworm.com/rss/comments.php?id=5233608 Thu, 01 Sep 2011 04:00:00 +0100 5233608 http://www.medworm.com/index.php?rid=5129988&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01646.x Summary Using multiple historical trials with surrogate and true endpoints, we consider various models to predict the effect of treatment on a true endpoint in a target trial in which only a surrogate endpoint is observed. This predicted result is computed using (1) a prediction model (mixture, linear, or principal stratification) estimated from historical trials and the surrogate endpoint of the target trial and (2) a random extrapolation error estimated from successively leaving out each trial among the historical trials. The method applies to either binary outcomes or survival to a particular time that is computed from censored survival data. We compute a 95% confidence interval for the predicted result and validate its coverage using simulation. To summarize the additional uncertainty ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5129988 Fri, 12 Aug 2011 23:00:00 +0100 5129988 http://www.medworm.com/index.php?rid=5124475&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01645.x Summary We propose an online binary classification procedure for cases when there is uncertainty about the model to use and parameters within a model change over time. We account for model uncertainty through dynamic model averaging, a dynamic extension of Bayesian model averaging in which posterior model probabilities may also change with time. We apply a state‐space model to the parameters of each model and we allow the data‐generating model to change over time according to a Markov chain. Calibrating a “forgetting” factor accommodates different levels of change in the data‐generating mechanism. We propose an algorithm that adjusts the level of forgetting in an online fashion using the posterior predictive distribution, and so accommodates various levels of change at different ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124475 Thu, 11 Aug 2011 23:00:00 +0100 5124475 http://www.medworm.com/index.php?rid=5124474&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01647.x Summary The evaluation of surrogate endpoints for primary use in future clinical trials is an increasingly important research area, due to demands for more efficient trials coupled with recent regulatory acceptance of some surrogates as ‘valid.’ However, little consideration has been given to how a trial that utilizes a newly validated surrogate endpoint as its primary endpoint might be appropriately designed. We propose a novel Bayesian adaptive trial design that allows the new surrogate endpoint to play a dominant role in assessing the effect of an intervention, while remaining realistically cautious about its use. By incorporating multitrial historical information on the validated relationship between the surrogate and clinical endpoints, then subsequently evaluating accumulating da... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124474 Thu, 11 Aug 2011 23:00:00 +0100 5124474 http://www.medworm.com/index.php?rid=5124473&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01649.x Summary Many statistical tests have been proposed for case–control data to detect disease association with multiple single nucleotide polymorphisms (SNPs) in linkage disequilibrium. The main reason for the existence of so many tests is that each test aims to detect one or two aspects of many possible distributional differences between cases and controls, largely due to the lack of a general and yet simple model for discrete genotype data. Here we propose a latent variable model to represent SNP data: the observed SNP data are assumed to be obtained by discretizing a latent multivariate Gaussian variate. Because the latent variate is multivariate Gaussian, its distribution is completely characterized by its mean vector and covariance matrix, in contrast to much more complex forms of a gen... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124473 Thu, 11 Aug 2011 23:00:00 +0100 5124473 http://www.medworm.com/index.php?rid=5124472&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01650.x Summary Despite recent flourish of proposals on variable selection, genome‐wide multiple loci mapping remains to be challenging. The majority of existing variable selection methods impose a model, and often the homoscedastic linear model, prior to selection. However, the true association between the phenotypical trait and the genetic markers is rarely known a priori, and the presence of epistatic interactions makes the association more complex than a linear relation. Model‐free variable selection offers a useful alternative in this context, but the fact that the number of markers p often far exceeds the number of experimental units n renders all the existing model‐free solutions that require n > p inapplicable. In this article, we examine a number of model‐free v... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124472 Thu, 11 Aug 2011 23:00:00 +0100 5124472 http://www.medworm.com/index.php?rid=5124471&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01652.x Summary We consider the problem of high‐dimensional regression under nonconstant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high‐dimensional analysis of genomic data sets. We propose a new methodology that allows nonconstant error variances for high‐dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124471 Thu, 11 Aug 2011 23:00:00 +0100 5124471 http://www.medworm.com/index.php?rid=5124470&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01653.x Summary We discuss identifiability and estimation of causal effects of a treatment in subgroups defined by a covariate that is sometimes missing due to death, which is different from a problem with outcomes censored by death. Frangakis et al. (2007, Biometrics 63, 641–662) proposed an approach for estimating the causal effects under a strong monotonicity (SM) assumption. In this article, we focus on identifiability of the joint distribution of the covariate, treatment and potential outcomes, show sufficient conditions for identifiability, and relax the SM assumption to monotonicity (M) and no‐interaction (NI) assumptions. We derive expectation–maximization algorithms for finding the maximum likelihood estimates of parameters of the joint distribution under different assumptions. ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124470 Thu, 11 Aug 2011 23:00:00 +0100 5124470 http://www.medworm.com/index.php?rid=5124469&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01654.x Summary RNA‐seq may replace gene expression microarrays in the near future. Using RNA‐seq, the expression of a gene can be estimated using the total number of sequence reads mapped to that gene, known as the total read count (TReC). Traditional expression quantitative trait locus (eQTL) mapping methods, such as linear regression, can be applied to TReC measurements after they are properly normalized. In this article, we show that eQTL mapping, by directly modeling TReC using discrete distributions, has higher statistical power than the two‐step approach: data normalization followed by linear regression. In addition, RNA‐seq provides information on allele‐specific expression (ASE) that is not available from microarrays. By combining the information from TReC and ASE, we can comput... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124469 Thu, 11 Aug 2011 23:00:00 +0100 5124469 http://www.medworm.com/index.php?rid=5124468&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01655.x Summary In applications that require cost efficiency, sample sizes are typically small so that the problem of empty strata may often occur in judgment poststratification (JPS), an important variant of balanced ranked set sampling. In this article, we consider estimation of population cumulative distribution functions (CDF) from JPS samples with empty strata. In the literature, the standard and restricted CDF estimators (Stokes and Sager, 1988, Journal of the American Statistical Association 83, 374381; Frey and Ozturk, 2011, Annals of the Institute of Statistical Mathematics, to appear) do not perform well when simply ignoring empty strata. In this article, we show that the original isotonized estimator (Ozturk, 2007, Journal of Nonparametric Statistics 19, 131–144) can handle ... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124468 Thu, 11 Aug 2011 23:00:00 +0100 5124468 http://www.medworm.com/index.php?rid=5035480&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01642.x Summary Pilot phases of a randomized clinical trial often suggest that a parametric model may be an accurate description of the trial’s longitudinal trajectories. However, parametric models are often not used for fear that they may invalidate tests of null hypotheses of equality between the experimental groups. Existing work has shown that when, for some types of data, certain parametric models are used, the validity for testing the null is preserved even if the parametric models are incorrect. Here, we provide a broader and easier to check characterization of parametric models that can be used to (i) preserve nonparametric validity of testing the null hypothesis, i.e., even when the models are incorrect, and (ii) increase power compared to the non‐ or semiparametric bounds when the mo... Biometrics journals http://www.medworm.com/rss/comments.php?id=5035480 Thu, 14 Jul 2011 23:00:00 +0100 5035480 http://www.medworm.com/index.php?rid=5035479&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01643.x We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well‐known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5035479 Thu, 14 Jul 2011 23:00:00 +0100 5035479 http://www.medworm.com/index.php?rid=5006446&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01621.x Summary Model choice in linear mixed‐effects models for longitudinal data is a challenging task. Apart from the selection of covariates, also the choice of the random effects and the residual correlation structure should be possible. Application of classical model choice criteria such as Akaike information criterion (AIC) or Bayesian information criterion is not obvious, and many versions do exist. In this article, a predictive cross‐validation approach to model choice is proposed based on the logarithmic and the continuous ranked probability score. In contrast to full cross‐validation, the model has to be fitted only once, which enables fast computations, even for large data sets. Relationships to the recently proposed conditional AIC are discussed. The methodology is applied to sea... Biometrics journals http://www.medworm.com/rss/comments.php?id=5006446 Tue, 05 Jul 2011 23:00:00 +0100 5006446 http://www.medworm.com/index.php?rid=5035482&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01625.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5035482 Tue, 28 Jun 2011 23:00:00 +0100 5035482 http://www.medworm.com/index.php?rid=4983355&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01623.x Summary We propose optimal choice of the design parameters for random discontinuation designs (RDD) using a Bayesian decision‐theoretic approach. We consider applications of RDDs to oncology phase II studies evaluating activity of cytostatic agents. The design consists of two stages. The preliminary open‐label stage treats all patients with the new agent and identifies a possibly sensitive subpopulation. The subsequent second stage randomizes, treats, follows, and compares outcomes among patients in the identified subgroup, with randomization to either the new or a control treatment. Several tuning parameters characterize the design: the number of patients in the trial, the duration of the preliminary stage, and the duration of follow‐up after randomization. We define a probability m... Biometrics journals http://www.medworm.com/rss/comments.php?id=4983355 Tue, 28 Jun 2011 23:00:00 +0100 4983355 http://www.medworm.com/index.php?rid=4983353&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01626.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4983353 Tue, 28 Jun 2011 23:00:00 +0100 4983353 http://www.medworm.com/index.php?rid=4983352&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01627.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4983352 Tue, 28 Jun 2011 23:00:00 +0100 4983352 http://www.medworm.com/index.php?rid=4951428&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01629.x Summary Dichotomization of continuous exposure variables is a common practice in medical and epidemiological research. The practice has been cautioned against on the grounds of efficiency and bias. Here we consider the consequences of dichotomization of a continuous covariate for the study of interactions. We show that when a continuous exposure has been dichotomized certain inferences concerning causal interactions can be drawn with regard to the original continuous exposure scale. Within the context of interaction analyses, dichotomization and the use of the results in this article can furthermore help prevent incorrect conclusions about the presence of interactions that result simply from erroneous modeling of the exposure variables. By considering different dichotomization points one c... Biometrics journals http://www.medworm.com/rss/comments.php?id=4951428 Sun, 19 Jun 2011 23:00:00 +0100 4951428 http://www.medworm.com/index.php?rid=4951427&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01639.x We describe a Bayesian quantile regression model that uses a confirmatory factor structure for part of the design matrix. This model is appropriate when the covariates are indicators of scientifically determined latent factors, and it is these latent factors that analysts seek to include as predictors in the quantile regression. We apply the model to a study of birth weights in which the effects of latent variables representing psychosocial health and actual tobacco usage on the lower quantiles of the response distribution are of interest. The models can be fit using an R package called factorQR. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951427 Sun, 19 Jun 2011 23:00:00 +0100 4951427 http://www.medworm.com/index.php?rid=4951426&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01640.x Summary Estimation of relative survival has become the first and the most basic step when reporting cancer survival statistics. Standard estimators are in routine use by all cancer registries. However, it has been recently noted that these estimators do not provide information on cancer mortality that is independent of the national general population mortality. Thus they are not suitable for comparison between countries. Furthermore, the commonly used interpretation of the relative survival curve is vague and misleading. The present article attempts to remedy these basic problems. The population quantities of the traditional estimators are carefully described and their interpretation discussed. We then propose a new estimator of net survival probability that enables the desired comparabili... Biometrics journals http://www.medworm.com/rss/comments.php?id=4951426 Sun, 19 Jun 2011 23:00:00 +0100 4951426 http://www.medworm.com/index.php?rid=4959309&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01634.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4959309 Sun, 12 Jun 2011 23:00:00 +0100 4959309 http://www.medworm.com/index.php?rid=4959306&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01638.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4959306 Sun, 12 Jun 2011 23:00:00 +0100 4959306 http://www.medworm.com/index.php?rid=4932434&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01630.x Summary Generalized linear models are a widely used method to obtain parametric estimates for the mean function. They have been further extended to allow the relationship between the mean function and the covariates to be more flexible via generalized additive models. However, the fixed variance structure can in many cases be too restrictive. The extended quasilikelihood (EQL) framework allows for estimation of both the mean and the dispersion/variance as functions of covariates. As for other maximum likelihood methods though, EQL estimates are not resistant to outliers: we need methods to obtain robust estimates for both the mean and the dispersion function. In this article, we obtain functional estimates for the mean and the dispersion that are both robust and smooth. The performance of ... Biometrics journals http://www.medworm.com/rss/comments.php?id=4932434 Sun, 12 Jun 2011 23:00:00 +0100 4932434 http://www.medworm.com/index.php?rid=4932433&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01631.x Summary Link‐tracing sampling designs can be used to study human populations that contain “hidden” groups who tend to be linked together by a common social trait. These links can be used to increase the sampling intensity of a hidden domain by tracing links from individuals selected in an initial wave of sampling to additional domain members. Chow and Thompson (2003, Survey Methodology 29, 197–205) derived a Bayesian model to estimate the size or proportion of individuals in the hidden population for certain link‐tracing designs. We propose an addition to their model that will allow for the modeling of a quantitative response. We assess properties of our model using a constructed population and a real population of at‐risk individuals, both of which contain two domains of h... Biometrics journals http://www.medworm.com/rss/comments.php?id=4932433 Sun, 12 Jun 2011 23:00:00 +0100 4932433 http://www.medworm.com/index.php?rid=4932432&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01632.x Summary Cross‐sectional HIV incidence estimation based on a sensitive and less‐sensitive test offers great advantages over the traditional cohort study. However, its use has been limited due to concerns about the false negative rate of the less‐sensitive test, reflecting the phenomenon that some subjects may remain negative permanently on the less‐sensitive test. Wang and Lagakos (2010, Biometrics 66, 864–874) propose an augmented cross‐sectional design that provides one way to estimate the size of the infected population who remain negative permanently and subsequently incorporate this information in the cross‐sectional incidence estimator. In an augmented cross‐sectional study, subjects who test negative on the less‐sensitive test in the cross‐sectional survey are... Biometrics journals http://www.medworm.com/rss/comments.php?id=4932432 Sun, 12 Jun 2011 23:00:00 +0100 4932432 http://www.medworm.com/index.php?rid=4932431&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01633.x Summary There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using metaanalytical methods for quantification of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semicompeting risks setting, where we model the region where the surrogate endpoint occurs before the true endpoint. Several estimation methods and attendant inferential procedures are presented. In addition, between‐ and within‐trial methods for evaluating surrogacy ar... Biometrics journals http://www.medworm.com/rss/comments.php?id=4932431 Sun, 12 Jun 2011 23:00:00 +0100 4932431 http://www.medworm.com/index.php?rid=4932430&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01634.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4932430 Sun, 12 Jun 2011 23:00:00 +0100 4932430 http://www.medworm.com/index.php?rid=4932429&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01635.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4932429 Sun, 12 Jun 2011 23:00:00 +0100 4932429 http://www.medworm.com/index.php?rid=4932428&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01637.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4932428 Sun, 12 Jun 2011 23:00:00 +0100 4932428 http://www.medworm.com/index.php?rid=5155848&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01651.x Summary We provide four‐parameter families of distributions on the circle which are unimodal and display the widest ranges of both skewness and peakedness yet available. Our approach is to transform the scale of a generating distribution, such as the von Mises, using various nontrivial extensions of an approach first used in Batschelet’s (1981, Circular Statistics in Biology) book. The key is to employ inverses of Batschelet‐type transformations in certain ways; these exhibit considerable advantages over direct Batschelet transformations. The skewness transformation is especially appealing as it has no effect on the normalizing constant. As well as a variety of interesting theoretical properties, when likelihood inference is explored these distributions display orthogonality betwee... Biometrics journals http://www.medworm.com/rss/comments.php?id=5155848 Tue, 31 May 2011 23:00:00 +0100 5155848 http://www.medworm.com/index.php?rid=5129987&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01648.x We present a three‐component mixture model for BNI, with the components representing premature, at‐risk, and healthy births. The BNI distribution is derived from a stochastic model of fetal development proposed by Whitmore and Su (2007, Lifetime Data Analysis 13, 161–190) and takes the form of a mixture of inverse Gaussian distributions. We present a noncentral t‐distribution as a model for BDI. BNI and BDI are also well suited for making comparisons of birth outcomes in different reference populations. A simple z‐score and t‐score are proposed for such comparisons. The BNI and BDI distributions can be estimated for births in any reference population of interest using threshold regression. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5129987 Tue, 31 May 2011 23:00:00 +0100 5129987 http://www.medworm.com/index.php?rid=5124467&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01657.x Summary Random effects models are widely used in population pharmacokinetics and dose‐finding studies. However, when more than one observation is taken per patient, the presence of correlated observations (due to shared random effects and possibly residual serial correlation) usually makes the explicit determination of optimal designs difficult. In this article, we introduce a class of multiplicative algorithms to be able to handle correlated data and thus allow numerical calculation of optimal experimental designs in such situations. In particular, we demonstrate its application in a concrete example of a crossover dose‐finding trial, as well as in a typical population pharmacokinetics example. Additionally, we derive a lower bound for the efficiency of any given design in this contex... Biometrics journals http://www.medworm.com/rss/comments.php?id=5124467 Tue, 31 May 2011 23:00:00 +0100 5124467 http://www.medworm.com/index.php?rid=5035478&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01644.x Summary Since the early 1940s, group testing (pooled testing) has been used to reduce costs in a variety of applications, including infectious disease screening, drug discovery, and genetics. In such applications, the goal is often to classify individuals as positive or negative using initial group testing results and the subsequent process of decoding of positive pools. Many decoding algorithms have been proposed, but most fail to acknowledge, and to further exploit, the heterogeneous nature of the individuals being screened. In this article, we use individuals’ risk probabilities to formulate new informative decoding algorithms that implement Dorfman retesting in a heterogeneous population. We introduce the concept of “thresholding” to classify individuals as “high” or “low r... Biometrics journals http://www.medworm.com/rss/comments.php?id=5035478 Tue, 31 May 2011 23:00:00 +0100 5035478 http://www.medworm.com/index.php?rid=5006445&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01622.x Summary For group‐randomized trials, randomization inference based on rank statistics provides robust, exact inference against nonnormal distributions. However, in a matched‐pair design, the currently available rank‐based statistics lose significant power compared to normal linear mixed model (LMM) test statistics when the LMM is true. In this article, we investigate and develop an optimal test statistic over all statistics in the form of the weighted sum of signed Mann‐Whitney‐Wilcoxon statistics under certain assumptions. This test is almost as powerful as the LMM even when the LMM is true, but it is much more powerful for heavy tailed distributions. A simulation study is conducted to examine the power. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=5006445 Tue, 31 May 2011 23:00:00 +0100 5006445 http://www.medworm.com/index.php?rid=4983351&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01628.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4983351 Tue, 31 May 2011 23:00:00 +0100 4983351 http://www.medworm.com/index.php?rid=4959305&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01636.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4959305 Tue, 31 May 2011 23:00:00 +0100 4959305 http://www.medworm.com/index.php?rid=4951438&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01616.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951438 Tue, 31 May 2011 23:00:00 +0100 4951438 http://www.medworm.com/index.php?rid=4951437&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01615.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951437 Tue, 31 May 2011 23:00:00 +0100 4951437 http://www.medworm.com/index.php?rid=4951436&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01614.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951436 Tue, 31 May 2011 23:00:00 +0100 4951436 http://www.medworm.com/index.php?rid=4951435&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01613.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951435 Tue, 31 May 2011 23:00:00 +0100 4951435 http://www.medworm.com/index.php?rid=4951434&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01612.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951434 Tue, 31 May 2011 23:00:00 +0100 4951434 http://www.medworm.com/index.php?rid=4951433&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01611.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951433 Tue, 31 May 2011 23:00:00 +0100 4951433 http://www.medworm.com/index.php?rid=4951432&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01610.x (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951432 Tue, 31 May 2011 23:00:00 +0100 4951432 http://www.medworm.com/index.php?rid=4951431&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01609.x Handbook of Spatial Statistics(A. E. Gelfand, P. J. Diggle, M. Fuentes, and P. Guttorp, Editors)Daniel CommengesComputational Statistics(J. E. Gentle)Thomas LumleyBayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation(M. T. Tan, G.‐L. Tian, and K. W. Ng)Alessandra MatteiA First Course in Bayesian Statistical Methods(P. D. Hoff)Dalene StanglEnvironmental and Ecological Statistics with R(S. S. Qian)Andrew FinleyA Modern Approach to Regression with R(S. J. Sheather)Mervyn G. MarasingheExercises and Solutions in Biostatistical Theory(L. L. Kupper, B. H. Neelon, and S. M. O’Brien)Scott S. Emersonggplot2: Elegant Graphics for Data Analysis(H. Wickham)Leland Wilkinson (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951431 Tue, 31 May 2011 23:00:00 +0100 4951431 http://www.medworm.com/index.php?rid=4951430&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2010.01474_2.x Summary In this rejoinder, we discuss the impact of misspecifying the random effects distribution on inferences obtained from generalized linear mixed models (GLMMs). Special attention is paid to the power of the tests for the fixed‐effect parameters. To study this misspecification, researchers often use simulation designs in which several choices for the true underlying random‐effects distribution are considered, while the assumed distribution is kept fixed. Neuhaus, McCulloch, and Boylan (2010, Biometrics 00, 000–000) argue that a logically correct approach should consist of varying the assumed, fitted distribution, while holding the true fixed. We argue that both simulation designs can bring valuable insights into the impact of the misspecification. Furthermore, using both des... Biometrics journals http://www.medworm.com/rss/comments.php?id=4951430 Tue, 31 May 2011 23:00:00 +0100 4951430 http://www.medworm.com/index.php?rid=4951429&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2010.01474_1.x We present logically correct simulation studies that demonstrate little increase in Type II error, consistent with the earlier work that shows little effect due to misspecification. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4951429 Tue, 31 May 2011 23:00:00 +0100 4951429 http://www.medworm.com/index.php?rid=4951425&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01641.x Summary We develop a Bayesian approach to a calibration problem with one interested covariate subject to multiplicative measurement errors. Our work is motivated by a stem cell study with the objective of establishing the recommended minimum doses for stem cell engraftment after a blood transplant. When determining a safe stem cell dose based on the prefreeze samples, the postcryopreservation recovery rate enters in the model as a multiplicative measurement error term, as shown in the model (2). We examine the impact of ignoring measurement errors in terms of asymptotic bias in the regression coefficient. According to the general structure of data available in practice, we propose a two‐stage Bayesian method to perform model estimation via R2WinBUGS (Sturtz, Ligges, and Gelman, 2005, J... Biometrics journals http://www.medworm.com/rss/comments.php?id=4951425 Tue, 31 May 2011 23:00:00 +0100 4951425 http://www.medworm.com/index.php?rid=4882772&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01607.x Summary Genetic anticipation, described by earlier age of onset (AOO) and more aggressive symptoms in successive generations, is a phenomenon noted in certain hereditary diseases. Its extent may vary between families and/or between mutation subtypes known to be associated with the disease phenotype. In this article, we posit a Bayesian approach to infer genetic anticipation under flexible random effects models for censored data that capture the effect of successive generations on AOO. Primary interest lies in the random effects. Misspecifying the distribution of random effects may result in incorrect inferential conclusions. We compare the fit of four‐candidate random effects distributions via Bayesian model fit diagnostics. A related statistical issue here is isolating the confounding e... Biometrics journals http://www.medworm.com/rss/comments.php?id=4882772 Mon, 30 May 2011 23:00:00 +0100 4882772 http://www.medworm.com/index.php?rid=4882771&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01608.x Summary In clinical trials, a biomarker (S ) that is measured after randomization and is strongly associated with the true endpoint (T) can often provide information about T and hence the effect of a treatment (Z ) on T. A useful biomarker can be measured earlier than T and cost less than T. In this article, we consider the use of S as an auxiliary variable and examine the information recovery from using S for estimating the treatment effect on T, when S is completely observed and T is partially observed. In an ideal but often unrealistic setting, when S satisfies Prentice’s definition for perfect surrogacy, there is the potential for substantial gain in precision by using data from S to estimate the treatment effect on T. When S is not clo... Biometrics journals http://www.medworm.com/rss/comments.php?id=4882771 Mon, 30 May 2011 23:00:00 +0100 4882771 http://www.medworm.com/index.php?rid=4882770&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01617.x This article explores effective implementation of split‐plot designs in serial dilution bioassay using robots. We show that the shortest path for a robot to fill plate wells for a split‐plot design is equivalent to the shortest common supersequence problem in combinatorics. We develop an algorithm for finding the shortest common supersequence, provide an R implementation, and explore the distribution of the number of steps required to implement split‐plot designs for bioassay through simulation. We also show how to construct collections of split plots that can be filled in a minimal number of steps, thereby demonstrating that split‐plot designs can be implemented with nearly the same effort as strip‐plot designs. Finally, we provide guidelines for modeling data that result from t... Biometrics journals http://www.medworm.com/rss/comments.php?id=4882770 Mon, 30 May 2011 23:00:00 +0100 4882770 http://www.medworm.com/index.php?rid=4882769&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01618.x Summary In microarray screening for differentially expressed genes using multiple testing, assessment of power or sample size is of particular importance to ensure that few relevant genes are removed from further consideration prematurely. In this assessment, adequate estimation of the effect sizes of differentially expressed genes is crucial because of its substantial impact on power and sample‐size estimates. However, conventional methods using top genes with largest observed effect sizes would be subject to overestimation due to random variation. In this article, we propose a simple estimation method based on hierarchical mixture models with a nonparametric prior distribution to accommodate random variation and possible large diversity of effect sizes across differential genes, separa... Biometrics journals http://www.medworm.com/rss/comments.php?id=4882769 Mon, 30 May 2011 23:00:00 +0100 4882769 http://www.medworm.com/index.php?rid=4882768&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01619.x Summary We propose a new criterion for confounder selection when the underlying causal structure is unknown and only limited knowledge is available. We assume all covariates being considered are pretreatment variables and that for each covariate it is known (i) whether the covariate is a cause of treatment, and (ii) whether the covariate is a cause of the outcome. The causal relationships the covariates have with one another is assumed unknown. We propose that control be made for any covariate that is either a cause of treatment or of the outcome or both. We show that irrespective of the actual underlying causal structure, if any subset of the observed covariates suffices to control for confounding then the set of covariates chosen by our criterion will also suffice. We show that other, co... Biometrics journals http://www.medworm.com/rss/comments.php?id=4882768 Mon, 30 May 2011 23:00:00 +0100 4882768 http://www.medworm.com/index.php?rid=4741803&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01601.x We present a general probabilistic ICA (PICA) model that can accommodate varying group structures of multisubject spatiotemporal processes. An advantage of the proposed model is that it can flexibly model various types of group structures in different underlying neural source signals and under different experimental conditions in fMRI studies. A maximum likelihood (ML) method is used for estimating this general group ICA model. We propose two expectation–maximization (EM) algorithms to obtain the ML estimates. The first method is an exact EM algorithm, which provides an exact E‐step and an explicit noniterative M‐step. The second method is a variational approximation EM algorithm, which is computationally more efficient than the exact EM. In simulation studies, we first compare the p... Biometrics journals http://www.medworm.com/rss/comments.php?id=4741803 Thu, 21 Apr 2011 23:00:00 +0100 4741803 http://www.medworm.com/index.php?rid=4741802&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01602.x We present in this article a model‐based approach for better identification of differentially expressed genes by incorporating data from different studies. The model can accommodate in a seamless fashion a wide range of studies including those performed at different platforms by fitting each data with different set of parameters, and/or under different but overlapping biological conditions. Model‐based inferences can be done in an empirical Bayes' fashion. Because of the information sharing among studies, the joint analysis dramatically improves inferences based on individual analysis. Simulation studies and real data examples are presented to demonstrate the effectiveness of the proposed approach under a variety of complications that often arise in practice. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4741802 Thu, 21 Apr 2011 23:00:00 +0100 4741802 http://www.medworm.com/index.php?rid=4741801&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01603.x Summary Recently a new definition of surrogate endpoint, the “principal surrogate,” was proposed based on causal associations between treatment effects on the biomarker and on the clinical endpoint. Despite its appealing interpretation, limited research has been conducted to evaluate principal surrogates, and existing methods focus on risk models that consider a single biomarker. How to compare principal surrogate value of biomarkers or general risk models that consider multiple biomarkers remains an open research question. We propose to characterize a marker or risk model’s principal surrogate value based on the distribution of risk difference between interventions. In addition, we propose a novel summary measure (the standardized total gain) that can be used to compare markers and ... Biometrics journals http://www.medworm.com/rss/comments.php?id=4741801 Thu, 21 Apr 2011 23:00:00 +0100 4741801 http://www.medworm.com/index.php?rid=4741800&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01605.x Summary Next‐generation sequencing (NGS) technology generates millions of short reads, which provide valuable information for various aspects of cellular activities and biological functions. A key step in NGS applications (e.g., RNA‐Seq) is to map short reads to correct genomic locations within the source genome. While most reads are mapped to a unique location, a significant proportion of reads align to multiple genomic locations with equal or similar numbers of mismatches; these are called multireads. The ambiguity in mapping the multireads may lead to bias in downstream analyses. Currently, most practitioners discard the multireads in their analysis, resulting in a loss of valuable information, especially for the genes with similar sequences. To refine the read mapping, we develop a... Biometrics journals http://www.medworm.com/rss/comments.php?id=4741800 Thu, 21 Apr 2011 23:00:00 +0100 4741800 http://www.medworm.com/index.php?rid=4732713&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01586.x Summary HIV RNA viral load measures are often subjected to some upper and lower detection limits depending on the quantification assays. Hence, the responses are either left or right censored. Linear (and nonlinear) mixed‐effects models (with modifications to accommodate censoring) are routinely used to analyze this type of data and are based on normality assumptions for the random terms. However, those analyses might not provide robust inference when the normality assumptions are questionable. In this article, we develop a Bayesian framework for censored linear (and nonlinear) models replacing the Gaussian assumptions for the random terms with normal/independent (NI) distributions. The NI is an attractive class of symmetric heavy‐tailed densities that includes the normal, Student's‐... Biometrics journals http://www.medworm.com/rss/comments.php?id=4732713 Mon, 18 Apr 2011 23:00:00 +0100 4732713 http://www.medworm.com/index.php?rid=4732712&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01595.x Summary We consider the problem of estimating the number of species (denoted by S) of a biological community located in a region divided into n quadrats. To address this question, different hierarchical parametric approaches have been recently developed. Despite a detailed modeling of the underlying biological processes, they all have some limitations. Indeed, some assume that n is theoretically infinite; as a result, n and the sampling fraction are not a part of such models. Others require some prior information on S to be efficiently implemented. Our approach is more general in that it applies without limitation on the size of n, and it can be used in the presence, as well as in the absence, of prior information on S. Moreover, it can be viewed as an extension of the approach of Dorazio ... Biometrics journals http://www.medworm.com/rss/comments.php?id=4732712 Mon, 18 Apr 2011 23:00:00 +0100 4732712 http://www.medworm.com/index.php?rid=4732711&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01598.x Summary We propose in this article a powerful testing procedure for detecting a gene effect on a continuous outcome in the presence of possible gene–gene interactions (epistasis) in a gene set, e.g., a genetic pathway or network. Traditional tests for this purpose require a large number of degrees of freedom by testing the main effect and all the corresponding interactions under a parametric assumption, and hence suffer from low power. In this article, we propose a powerful kernel machine based test. Specifically, our test is based on a garrote kernel method and is constructed as a score test. Here, the term garrote refers to an extra nonnegative parameter that is multiplied to the covariate of interest so that our score test can be formulated in terms of this nonnegative parameter. A ke... Biometrics journals http://www.medworm.com/rss/comments.php?id=4732711 Mon, 18 Apr 2011 23:00:00 +0100 4732711 http://www.medworm.com/index.php?rid=4732710&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01599.x We present a Bayesian, semiparametric method that explicitly models the expected number of fish in each stratum as a smooth function of time. Results from the analysis of historical data from the migration of young Atlantic salmon (Salmo salar) along the Conne River, Newfoundland, and from a simulation study indicate that the new method provides more precise estimates of the population size and more accurate estimates of uncertainty than the currently available methods. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4732710 Mon, 18 Apr 2011 23:00:00 +0100 4732710 http://www.medworm.com/index.php?rid=4683041&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01593.x Summary Exact unconditional tests have been widely applied to test the difference between two probabilities for 2 × 2 matched‐pairs binary data with small sample size. In this context, Lloyd (2008, Biometrics 64, 716–723) proposed an E + M p‐value, that showed better performance than the existing M p‐value and C p‐value. However, the analytical calculation of the E + M p‐value requires that the Barnard convexity condition be satisfied; this can be challenging to prove theoretically. In this article, by a simple reformulation, we show that a weaker condition, conditional monotonicity, is sufficient to calculate all three p‐values (M, C, and E + M) and their corresponding exact sizes. Moreover, this conditional monotonicity condition... Biometrics journals http://www.medworm.com/rss/comments.php?id=4683041 Mon, 04 Apr 2011 23:00:00 +0100 4683041 http://www.medworm.com/index.php?rid=4683040&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01594.x Summary Measurement errors in covariates may result in biased estimates in regression analysis. Most methods to correct this bias assume nondifferential measurement errors—i.e., that measurement errors are independent of the response variable. However, in regression models for zero‐truncated count data, the number of error‐prone covariate measurements for a given observational unit can equal its response count, implying a situation of differential measurement errors. To address this challenge, we develop a modified conditional score approach to achieve consistent estimation. The proposed method represents a novel technique, with efficiency gains achieved by augmenting random errors, and performs well in a simulation study. The method is demonstrated in an ecology application. (Source... Biometrics journals http://www.medworm.com/rss/comments.php?id=4683040 Mon, 04 Apr 2011 23:00:00 +0100 4683040 http://www.medworm.com/index.php?rid=4683039&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01596.x Summary In practice, when analyzing data from a capture–recapture experiment it is tempting to apply modern advanced statistical methods to the observed capture histories. However, unless the analysis takes into account that the data have only been collected from individuals who have been captured at least once, the results may be biased. Without the development of new software packages, methods such as generalized additive models, generalized linear mixed models, and simulation–extrapolation cannot be readily implemented. In contrast, the partial likelihood approach allows the analysis of a capture–recapture experiment to be conducted using commonly available software. Here we examine the efficiency of this approach and apply it to several data sets. (Source: Biometrics) Biometrics journals http://www.medworm.com/rss/comments.php?id=4683039 Mon, 04 Apr 2011 23:00:00 +0100 4683039 http://www.medworm.com/index.php?rid=4669629&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01582.x Summary When novel scientific questions arise after longitudinal binary data have been collected, the subsequent selection of subjects from the cohort for whom further detailed assessment will be undertaken is often necessary to efficiently collect new information. Key examples of additional data collection include retrospective questionnaire data, novel data linkage, or evaluation of stored biological specimens. In such cases, all data required for the new analyses are available except for the new target predictor or exposure. We propose a class of longitudinal outcome‐dependent sampling schemes and detail a design corrected conditional maximum likelihood analysis for highly efficient estimation of time‐varying and time‐invariant covariate coefficients when resource limitations proh... Biometrics journals http://www.medworm.com/rss/comments.php?id=4669629 Fri, 01 Apr 2011 23:00:00 +0100 4669629 http://www.medworm.com/index.php?rid=4669628&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01584.x This article proposes a fully nonparametric approach for estimating the gap time hazard. Smoothing spline analysis of variance (ANOVA) decompositions are used to model the log gap time hazard as a joint function of gap time and covariates, and general frailty is introduced to account for between‐subject heterogeneity and within‐subject correlation. We estimate the nonparametric gap time hazard function and parameters in the frailty distribution using a combination of the Newton–Raphson procedure, the stochastic approximation algorithm (SAA), and the Markov chain Monte Carlo (MCMC) method. The convergence of the algorithm is guaranteed by decreasing the step size of parameter update and/or increasing the MCMC sample size along iterations. Model selection procedure is also developed to... Biometrics journals http://www.medworm.com/rss/comments.php?id=4669628 Fri, 01 Apr 2011 23:00:00 +0100 4669628 http://www.medworm.com/index.php?rid=4669627&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01587.x This article briefly reviews existing regularization methods for penalized least squares and likelihood for survival data and their extension to a certain class of penalized estimating function. We show that if one's goal is to estimate the entire regularized coefficient path using the observed survival data, then all current strategies fail for the Buckley–James estimating function. We propose a novel two‐stage method to estimate and restore the entire Dantzig‐regularized coefficient path for censored outcomes in a least‐squares framework. We apply our methods to a microarray study of lung andenocarcinoma with sample size n = 200 and p = 1036 gene predictors and find 10 genes that are consistently selected across different criteria and an additional 14 genes that merit... Biometrics journals http://www.medworm.com/rss/comments.php?id=4669627 Fri, 01 Apr 2011 23:00:00 +0100 4669627 http://www.medworm.com/index.php?rid=4610238&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01567.x Summary The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly because the appropriate asymptotic theory involves a problem with the number of parameters increasing with the number of observations. In this article, we develop a multistep procedure for the Sigmoidal models, ensuring consistent estimation of the concentration levels with full asymptotic efficiency. The results obtained in the article justify inferential procedures based on large sample approximations. Simulation studies and real data analysis are used in the article to illustrate the performance of the proposed method in finite s... Biometrics journals http://www.medworm.com/rss/comments.php?id=4610238 Fri, 18 Mar 2011 00:00:00 +0100 4610238 http://www.medworm.com/index.php?rid=4610237&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01585.x Summary A real‐time surveillance method is developed with emphasis on rapid and accurate detection of emerging outbreaks. We develop a model with relatively weak assumptions regarding the latent processes generating the observed data, ensuring a robust prediction of the spatiotemporal incidence surface. Estimation occurs via a local linear fitting combined with day‐of‐week effects, where spatial smoothing is handled by a novel distance metric that adjusts for population density. Detection of emerging outbreaks is carried out via residual analysis. Both daily residuals and AR model‐based detrended residuals are used for detecting abnormalities in the data given that either a large daily residual or an increasing temporal trend in the residuals signals a potential outbreak, with the ... Biometrics journals http://www.medworm.com/rss/comments.php?id=4610237 Fri, 18 Mar 2011 00:00:00 +0100 4610237 http://www.medworm.com/index.php?rid=4610236&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01588.x Summary In Western countries where food supply is satisfactory, consumers organize their diets around a large combination of foods. It is the purpose of this article to examine how recent nonnegative matrix factorization (NMF) techniques can be applied to food consumption data to understand these combinations. Such data are nonnegative by nature and of high dimension. The NMF model provides a representation of consumption data through latent vectors with nonnegative coefficients, that we call consumption systems (CS), in a small number. As the NMF approach may encourage sparsity of the data representation produced, the resulting CS are easily interpretable. Beyond the illustration of its properties we provide through a simple simulation result, the NMF method is applied to data issued from... Biometrics journals http://www.medworm.com/rss/comments.php?id=4610236 Fri, 18 Mar 2011 00:00:00 +0100 4610236 http://www.medworm.com/index.php?rid=4610235&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01589.x Summary Recurrent events are common in medical research for subjects who are followed for the duration of a study. For example, cardiovascular patients with an implantable cardioverter defibrillator (ICD) experience recurrent arrhythmic events that are terminated by shocks or antitachycardia pacing delivered by the device. In a published randomized clinical trial, a recurrent‐event model was used to study the effect of a drug therapy in subjects with ICDs, who were experiencing recurrent symptomatic arrhythmic events. Under this model, one expects the robust variance for the estimated treatment effect to diminish when the duration of the trial is extended, due to the additional events observed. However, as shown in this article, that is not always the case. We investigate this phenomenon... Biometrics journals http://www.medworm.com/rss/comments.php?id=4610235 Fri, 18 Mar 2011 00:00:00 +0100 4610235 http://www.medworm.com/index.php?rid=4610234&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01590.x Summary We propose an additive mixed effect model to analyze clustered failure time data. The proposed model assumes an additive structure and includes a random effect as an additional component. Our model imitates the commonly used mixed effect models in repeated measurement analysis but under the context of hazards regression; our model can also be considered as a parallel development of the gamma‐frailty model in additive model structures. We develop estimating equations for parameter estimation and propose a way of assessing the distribution of the latent random effect in the presence of large clusters. We establish the asymptotic properties of the proposed estimator. The small sample performance of our method is demonstrated via a large number of simulation studies. Finally, we appl... Biometrics journals http://www.medworm.com/rss/comments.php?id=4610234 Fri, 18 Mar 2011 00:00:00 +0100 4610234 http://www.medworm.com/index.php?rid=4590514&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01577.x Summary Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are est... Biometrics journals http://www.medworm.com/rss/comments.php?id=4590514 Mon, 14 Mar 2011 00:00:00 +0100 4590514 http://www.medworm.com/index.php?rid=4590513&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01578.x Summary In smoking cessation clinical trials, subjects commonly receive treatment and report daily cigarette consumption over a period of several weeks. Although the outcome at the end of this period is an important indicator of treatment success, substantial uncertainty remains on how an individual's smoking behavior will evolve over time. Therefore it is of interest to predict long‐term smoking cessation success based on short‐term clinical observations. We develop a Bayesian method for prediction, based on a cure‐mixture frailty model we proposed earlier, that describes the process of transition between abstinence and smoking. Specifically we propose a two‐stage prediction algorithm that first uses importance sampling to generate subject‐specific frailties from their posterior... Biometrics journals http://www.medworm.com/rss/comments.php?id=4590513 Mon, 14 Mar 2011 00:00:00 +0100 4590513 http://www.medworm.com/index.php?rid=4590512&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01579.x Summary In a recent paper, Gaugler and Akritas (unpublished manuscript) considered testing for no main effect in a two‐factor mixed effects design when the traditional assumptions do not hold. Here we extend the nonparametric modeling to the random effects design and consider the problem of testing for no interaction effect. The new models for these designs allow for dependence among the random effects, heteroscedasticity in the error and interaction terms, and do not require normality. At a more systemic level, these models differ from the classical ones in that they do not consider the random interaction term as an additional, extraneous source of variability. The proposed test procedure applies to settings where the random factor in the case of the mixed model or at least one of the r... Biometrics journals http://www.medworm.com/rss/comments.php?id=4590512 Mon, 14 Mar 2011 00:00:00 +0100 4590512 http://www.medworm.com/index.php?rid=4590511&cid=s_32040_70_f&fid=32040&url=http%3A%2F%2Fdx.doi.org%2F10.1111%252Fj.1541-0420.2011.01580.x Summary We consider treatment regimes in which an agent is administered continuously at a specified concentration until either a response is achieved or a predetermined maximum infusion time is reached. Response is an event defined to characterize therapeutic efficacy. A portion of the maximum planned total amount administered is given as an initial bolus. For such regimes, the amount of the agent received by the patient depends on the time to response. An additional complication when response is evaluated periodically rather than continuously is that the response time is interval censored. We address the problem of designing a clinical trial in which such response time data and a binary indicator of toxicity are used together to jointly optimize the concentration and the size of the bolus... Biometrics journals http://www.medworm.com/rss/comments.php?id=4590511 Mon, 14 Mar 2011 00:00:00 +0100 4590511