of the art at a given point in time from the author's perspective of the topic. To whom may the book concern? First, its main parts require a solid knowledge of statistical concepts like random variables, bias, variance, confidence intervals, and statistical tests, but also a background in statistical modeling, re-sampling, and model selection. Re-sampling iswell presented in "An Introduction to the Bootstrap" (Efron and Tibshirani, 1993) while "Statistical Learning with Sparsity" (Hastie et al., 2015) covers the modern aspects of modeling and model selection. On the practical side, knowledge about concepts of clinical trials and drug development like efficacy and safety, and randomization and blinding are helpful. "Statistical Issues in Drug Development" (Senn, 2007) covers many of these topics. Notwithstanding what is said above, parts of the book should be readable by a non-statistical audience, mainly the chapters on history and to a lesser extent on pitfalls. Chapters digging a bit deeper into methodology (those coming with a heavier load of equations) should be primarily appreciated by statisticians. With this in mind, clinicians and statisticians from the area of clinical development and regulation should benefit most, although the topic of subgroup analysis has a much wider scope"-- |