Chapman & Hall/CRC Biostatistics Series – serie

Real-World Evidence in Drug Development and Evaluation

Cure Models

Methods, Applications, and Implementation

Model-Assisted Bayesian Designs for Dose Finding and Optimization

Methods and Applications

Advanced Survival Models

Analysis of Incidence Rates

Applied Meta-Analysis with R and Stata

Controlled Epidemiological Studies

Signal Detection for Medical Scientists

Likelihood Ratio Test-based Methodology

Innovative Statistics in Regulatory Science

Cancer Clinical Trials

Current and Controversial Issues in Design and Analysis

Clinical Trial Optimization Using R

Data and Safety Monitoring Committees in Clinical Trials

Geospatial Health Data

Modeling and Visualization with R-INLA and Shiny

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare

Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS

Empirical Likelihood Method in Survival Analysis

Bayesian Modeling in Bioinformatics

Elementary Bayesian Biostatistics

Applied Statistical Designs for the Researcher

Generalized Linear Models

A Bayesian Perspective

Meta-Analysis in Medicine and Health Policy

R for Health Technology Assessment

Medical Statistics for Cancer Studies

Interface between Regulation and Statistics in Drug Development

Innovative Methods for Rare Disease Drug Development

Innovative Methods for Rare Disease Drug Development

Drug Development for Rare Diseases

Advanced Statistics in Regulatory Critical Clinical Initiatives

Simultaneous Global New Drug Development

Multi-Regional Clinical Trials after ICH E17