Full Description
This unique volume provides self-contained accounts of some recent trends in Biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions.The articles included in this volume are based on a careful selection of peer-reviewed papers, authored by eminent experts in the field, representing a well balanced mix of researchers from the academia, R&D sectors of government and the pharmaceutical industry.The book is also intended to give advanced graduate students and new researchers a scholarly overview of several research frontiers in biostatistics, which they can use to further advance the field through development of new techniques and results.
Contents
A New Adaptive Method to Control the False Discovery Rate; Adaptive Multiple Testing Procedures Under Positive Dependence; A False Discovery Rate Procedure for Categorical Data; A Distribution for P-Values; Conditional Nelson-Aalen and Kaplan-Meier Estimators with the Muller-Wang Boundary Kernel; The Inverse Censoring Weighted Approach for Estimation of Survival Functions from Left and Right Censored Data; Modeling Survival Data Using the Piecewise Exponential Model with Random Time Grid; Analysis of Recurrent Time-to-Event Data Under Dependent Censoring; Efficient Algorithms in Bayesian Binary Regression with Skew-Probit Link; M-Estimation Methods in Heteroscedastic Nonlinear Regression Model; Regression Analysis in Failure Time Mixture Models with Change Points According to Thresholds in a Covariate; Competing Risks Data: Design and Analysis; Comparative Genomic Analysis Using Information Theory; Statistical Modeling for Positron Emission Tomography; Subset Selection in Comparative Selection Trials; Using Latent Class Analysis in Medical Diagnosis.
