This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.
This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.
Includes examples of a wide variety of common statistical errors and misconceptions in medical data analysis and clinical trial design, with at least one alternative solution for each problem, to provide statistical tools that can be used in practice
Written in an informal style with technical content kept to a reasonably low level, making it accessible to non-statisticians as well as statisticians
Is the first book of its kind for the medical research community
Peter F. Thall
Adaptive randomization Analysis of medical experiments Bayesian statistics Bias correction Clinical trials Confounding Design of medical experiments Dose finding Dynamic treatment regimes Expansion cohorts Experimental design Hypothesis testing Monitoring toxicity P-value Phase I Trials