Statistical Thinking for Non-Statisticians in Drug Regulation, 2nd Edition
Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials.
It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials.
Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis.
Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.
Preface to Second Edition
Preface to First Edition
1 Basic ideas in clinical trial design
2 Sampling and inferential statistics
3 Confidence intervals and p-values
4 Tests for simple treatment comparisons
5 Adjusting the analysis
6 Regression and analysis of covariance
7 Intention-to-treat and analysis sets
8 Power and sample size
9 Statistical significance and clinical importance
10 Multiple testing
11 Non-parametric and related methods
12 Equivalence and non-inferiority
13 The analysis of survival data
14 Interim analysis and data monitoring committees
15 Bayesian statistics
16 Adaptive Designs
17 Observational studies
19 Methods for the Safety Analysis and Safety Monitoring
21 The role of statistics and statisticians