Description
Book SynopsisThis 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.
Table of ContentsA 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.
