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 'Biometrika' source. Sat, 10 Oct 2009 19:28:38 +0100 http://www.medworm.com/index.php?rid=2548220&cid=s_37829_70_f&fid=37829&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19543426%26dopt%3DAbstract Authors: Hu XJ, Lagakos SW, Lockhart RA We develop nonparametric estimation procedures for the marginal mean function of a counting process based on periodic observations, using two types of self-consistent estimating equations. The first is derived from the likelihood studied in Wellner & Zhang (2000), assuming a Poisson counting process, and gives a nondecreasing estimator, which is the same as the nonparametric maximum likelihood estimator of Wellner & Zhang and thus is consistent without the Poisson assumption. Motivated by the construction of parametric generalized estimating equations, the second type is a set of data-adaptive quasi-score functions, which are likelihood estimating functions under a mixed-Poisson assumption. We evaluate the procedures via simulation, and i... Biometrika journals http://www.medworm.com/rss/comments.php?id=2548220 Sun, 28 Jun 2009 05:16:02 +0100 2548220 http://www.medworm.com/index.php?rid=2242961&cid=s_37829_70_f&fid=37829&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19262739%26dopt%3DAbstract Authors: Rodríguez A, Dunson DB, Gelfand AE In many modern experimental settings, observations are obtained in the form of functions, and interest focuses on inferences on a collection of such functions. We propose a hierarchical model that allows us to simultaneously estimate multiple curves nonparametrically by using dependent Dirichlet Process mixtures of Gaussians to characterize the joint distribution of predictors and outcomes. Function estimates are then induced through the conditional distribution of the outcome given the predictors. The resulting approach allows for flexible estimation and clustering, while borrowing information across curves. We also show that the function estimates we obtain are consistent on the space of integrable functions. As an illustration, we con... Biometrika journals http://www.medworm.com/rss/comments.php?id=2242961 Sat, 07 Mar 2009 19:02:45 +0100 2242961 http://www.medworm.com/index.php?rid=2042750&cid=s_37829_70_f&fid=37829&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D19079778%26dopt%3DAbstract Authors: Li Y, Prentice RL, Lin X We consider a class of semiparametric normal transformation models for right censored bivariate failure times. Nonparametric hazard rate models are transformed to a standard normal model and a joint normal distribution is assumed for the bivariate vector of transformed variates. A semiparametric maximum likelihood estimation procedure is developed for estimating the marginal survival distribution and the pairwise correlation parameters. This produces an efficient estimator of the correlation parameter of the semiparametric normal transformation model, which characterizes the bivariate dependence of bivariate survival outcomes. In addition, a simple positive-mass-redistribution algorithm can be used to implement the estimation procedures. Since the like... Biometrika journals http://www.medworm.com/rss/comments.php?id=2042750 Mon, 01 Dec 2008 05:00:00 +0100 2042750 http://www.medworm.com/index.php?rid=1807211&cid=s_37829_70_f&fid=37829&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18800173%26dopt%3DAbstract Authors: Dunson DB, Park JH We propose a class of kernel stick-breaking processes for uncountable collections of dependent random probability measures. The process is constructed by first introducing an infinite sequence of random locations. Independent random probability measures and beta-distributed random weights are assigned to each location. Predictor-dependent random probability measures are then constructed by mixing over the locations, with stick-breaking probabilities expressed as a kernel multiplied by the beta weights. Some theoretical properties of the process are described, including a covariate-dependent prediction rule. A retrospective Markov chain Monte Carlo algorithm is developed for posterior computation, and the methods are illustrated using a simulated example and ... Biometrika journals http://www.medworm.com/rss/comments.php?id=1807211 Fri, 19 Sep 2008 18:00:29 +0100 1807211 http://www.medworm.com/index.php?rid=1715149&cid=s_37829_70_f&fid=37829&url=http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fentrez%2Fquery.fcgi%3Ftmpl%3DNoSidebarfile%26db%3DPubMed%26cmd%3DRetrieve%26list_uids%3D18629347%26dopt%3DAbstract Authors: Hubbard AE, Laan MJ SummaryWe propose a new causal parameter, which is a natural extension of existing approaches to causal inference such as marginal structural models. Modelling approaches are proposed for the difference between a treatment-specific counterfactual population distribution and the actual population distribution of an outcome in the target population of interest. Relevant parameters describe the effect of a hypothetical intervention on such a population and therefore we refer to these models as population intervention models. We focus on intervention models estimating the effect of an intervention in terms of a difference and ratio of means, called risk difference and relative risk if the outcome is binary. We provide a class of inverse-probability-of-treatment... Biometrika journals http://www.medworm.com/rss/comments.php?id=1715149 Tue, 19 Aug 2008 19:04:30 +0100 1715149