Handbook of statistical methods for randomized controlled trials 

 - New York  Routledge  2021 
 - xxxiii, 620 p. 
 - Chapman & Hall/CRC Handbooks of Modern Statistical Methods .
<br/><br/> Table of contents:<br/>Part I. Introduction to Randomized, Controlled Trials<br/><br/>1. Introduction<br/>KyungMann Kim<br/><br/>Part II. Analytic Methods for Randomized, Controlled Trials<br/><br/>2. Dichotomous and ordinal: chi-square and Fisher's exact tests and binary regression models<br/>Garrett Fitzmaurice, Stuart Lipsitz<br/><br/>3. Continuous: t-test, Wilcoxon-test, and linear or non-linear regression models<br/>Fang-Shu Ou<br/><br/>4. Time to event subject to censoring: logrank test, Kaplan-Meier estimation and Cox proportional hazards regression models<br/>Daniel Scharfstein, Yuxin Zhu, Anastasios Tsiatis<br/><br/>5. Count: Poisson and negative binomial regression models<br/>Jianguo "Tony" Sun, Xin He<br/><br/>6. Longitudinal: Linear and generalized linear mixed models, GEE<br/>Myunghee Cho Paik, Soeun Kim<br/><br/>7. Recurrent events<br/>Richard Cook, Yujie Zhong<br/><br/>8. Cross-over design<br/>Stephen Senn<br/><br/>9. Factorial design<br/>Bibhas Chakraborty, Palash Ghosh<br/><br/>10. Cluster randomized design<br/>Martin Bland, Mona Kanaan<br/><br/>11. Randomization, stratification, and outcome-adaptive allocation<br/>Oleksandr Sverdlov, Yevgen Ryeznik<br/><br/>12. Sample size estimation and power analysis: Dichotomous, ordinal, continuous and count<br/>Keaven Anderson, Oliver Bautista<br/><br/>13. Sample size estimation and power analysis: Time-to-event data subject to censoring<br/>Keaven Anderson, Oliver Bautista<br/><br/>14. Sample size estimation and power analysis: Longitudinal data<br/>Sin-Ho Jung<br/><br/>15. Group sequential methods, triangular methods and stochastic curtailments<br/>Michael Proschan<br/><br/>16. Sample size re-estimation<br/>Tim Friede, Tobias Mütze<br/><br/>17. Adaptive designs<br/>Gernot Wassmer, Franz Koenig, Martin Posch<br/><br/>18. Multiple testing<br/>Jason Hsu, Yi Liu, Szu-Yu Tang<br/><br/>19. Subgroup analysis<br/>Rui Wang<br/><br/>20. Competing risks<br/>Haesook Kim<br/><br/>21. Joint models for longitudinal markers and clinical outcomes<br/>Helene Jacqmin-Gadda, Cécile Proust-Lima, Loïc Ferrer<br/><br/>22. Sequential multiple assignment randomization trial (SMART) for dynamic treatment allocation<br/>Michael Kosorok, Emily Butler<br/><br/>23. Safety data analysis<br/>Amy Xia, Brenda Crowe, Jesse Berlin<br/><br/>24. Non-inferiority trials<br/>Brian Wiens<br/><br/>25. Incorporating historical data into RCTs<br/>Heinz Schmidli, Sandro Gsteiger, Beat Neuenschwander<br/><br/>26. Validation of surrogate outcomes<br/>Geert Molenberghs<br/><br/><br/>[https://www.routledge.com/Handbook-of-Statistical-Methods-for-Randomized-Controlled-Trials/Kim-Bretz-Cheung-Hampson/p/book/9781032009100] 
<br/><br/> Statistical concepts provide scientific framework in experimental studies, including randomized controlled trials. In order to design, monitor, analyze and draw conclusions scientifically from such clinical trials, clinical investigators and statisticians should have a firm grasp of the requisite statistical concepts. The Handbook of Statistical Methods for Randomized Controlled Trials presents these statistical concepts in a logical sequence from beginning to end and can be used as a textbook in a course or as a reference on statistical methods for randomized controlled trials.<br/><br/>Part I provides a brief historical background on modern randomized controlled trials and introduces statistical concepts central to planning, monitoring and analysis of randomized controlled trials. Part II describes statistical methods for analysis of different types of outcomes and the associated statistical distributions used in testing the statistical hypotheses regarding the clinical questions. Part III describes some of the most used experimental designs for randomized controlled trials including the sample size estimation necessary in planning. Part IV describe statistical methods used in interim analysis for monitoring of efficacy and safety data. Part V describe important issues in statistical analyses such as multiple testing, subgroup analysis, competing risks and joint models for longitudinal markers and clinical outcomes. Part VI addresses selected miscellaneous topics in design and analysis including multiple assignment randomization trials, analysis of safety outcomes, non-inferiority trials, incorporating historical data, and validation of surrogate outcomes.<br/><br/>(https://www.routledge.com/Handbook-of-Statistical-Methods-for-Randomized-Controlled-Trials/Kim-Bretz-Cheung-Hampson/p/book/9781032009100) 
<br/><br/><label>ISBN: </label>9781032009100 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Medicine--Statistical method
<br/><br/><label>Dewey Class. No.: </label>610.724  / KIM