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Provides analysis of data from dynamic treatment regimen study design, cost-effectiveness analysis, analysis of genomic data, and causal inference to
Addresses confounding issues such as concurrent medication use and mechanism of action using marginal structural and structural equation models.
This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. Starting with survival data analysis, this book transitions from such a classic topic to modern issues by stepping through diagnostic test and instrument assessment, sequential and dynamic treatment regimen, cost-effectiveness evaluation, equivalence testing. As some type of cancer such as the effect of smoking on lung cancer cannot be studied using randomized trials, a chapter on analysis of non-randomized studies is also included. The book concludes with a chapter discussing the opportunities and challenges that lie ahead in developing on person-centered treatment regimens.
The book provides an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out the analyses. Medical researchers with some background in clinical trial design and regression analysis as well as biostatisticians will find this book informative and helpful.
Content Level »Research
Keywords »bioinformatics - biostatistics - cancer clinical trials - longitudinal data analysis - survival analysis