Functional Data Analysis in Biometrics and Biostatistics

Marginalized transition models and likelihood inference for longitudinal categorical data.

Marginal generalized linear models are now frequently used for the analysis of longitudinal data. Semiparametric inference for marginal models was introduced by Liang and Zeger (1986, Biometrics 73, 13-22). This article develops a general parametric class of serial dependence models that permits likelihood-based marginal regression analysis of binary response data. The methods naturally extend ...

Markov chains and semi-Markov models in time-to-event analysis.

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models...

Likelihood Reweighting Methods to Reduce Potential Bias in Noninferiority Trials Which Rely on Historical Data to Make

LIKELIHOOD REWEIGHTING METHODS TO REDUCE POTENTIAL BIAS IN NONINFERIORITY TRIALS WHICH RELY ON HISTORICAL DATA TO MAKE INFERENCE: By Lei Nie, Zhiwei Zhang*, Daniel Rubin, Jianxiong Chu Division of Biometrics IV, Office of Biostatistics/CDER/FDA 10903 New Hampshire Avenue, Silver Spring, MD 20993 Division of Biostatistics, Office of Surveillance and Biometrics/CDRH/FDA, 10903 New Hampshire Avenu...

Biometrics - How To Render Portable Data Security Convenient

On Bayesian Inference with Complex Survey Data.

Submit Manuscript | http://medcraveonline.com on updating assumed prior distributions with observed data likelihood. Much of this disconnect may be a function of differing goals; Bayesian approaches are focused on reliable statistical models [8] rather than on assessing the degree to which their estimates are nationally representative or not. However, Bayesian approaches, which have been succes...