Handbook of Statistical Methods for Randomized Controlled Trials

Herausgeber: Kim, Kyungmann; Cheung, Ying Kuen K; Bretz, Frank

• Gebundenes Buch

Produktbeschreibung

This handbook is intended to serve as a reference text on statistical methods for randomized controlled trials. It can be used as a textbook for a graduate course in statistical methods for randomized controlled trials as well as a reference for those involved in the design, monitoring and analysis of randomized controlled trials.

Produktdetails

• Verlag: Taylor and Francis
• Seitenzahl: 654
• Erscheinungstermin: 23. August 2021
• Englisch
• Abmessung: 254mm x 178mm x 35mm
• Gewicht: 1343g
• ISBN-13: 9781498714624
• ISBN-10: 1498714625
• Artikelnr.: 59989453

Autorenporträt

KyungMann Kim is Professor of Biostatistics and Statistics and Director of Clinical Trials Program, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison. He is a former associate editor of Biometrics and an elected Fellow of the American Statistical Association, the Society for Clinical Trials, and the American Association for Advancement of Science. Frank Bretz is a Distinguished Quantitative Research Scientist at Novartis. He is also an Adjunct Professor at the Hannover Medical School (Germany) and the Medical University Vienna (Austria). He is a former editor-in-chief of Statistics in Biopharmaceutical Research. a Fellow of the American Statistical Association, and a recipient of the Susanne-Dahms-Medal from the German Region of the International Biometric Society. Ying Kuen (Ken) Cheung is Professor of Biostatistics and Associate Dean for Faculty in the Mailman School of Public Health at Columbia University. He is a recipient of the IBM Faculty Award on Big Data and Analytics. He is a Fellow of the American Statistical Association and a Fellow of the New York Academy of Medicine. Lisa Hampson is a Director in Statistical Methodology at Novartis.

Inhaltsangabe

Part I. Introduction to Randomized, Controlled Trials. 1. Introduction.
Part II. Analytic Methods for Randomized, Controlled Trials. 2. Dichotomous
and ordinal: chi-square and Fisher's exact tests and binary regression
models. 3. Continuous: t-test, Wilcoxon-test, and linear or non-linear
regression models. 4. Time to event subject to censoring: logrank test,
Kaplan-Meier estimation and Cox proportional hazards regression models. 5.
Count: Poisson and negative binomial regression models. 6. Longitudinal:
Linear and generalized linear mixed models, GEE. 7. Recurrent events. 8.
Cross-over design. 9. Factorial design. 10. Cluster randomized design. 11.
Randomization, stratification, and outcome-adaptive allocation. 12. Sample
size estimation and power analysis: Dichotomous, ordinal, continuous and
count. 13. Sample size estimation and power analysis: Time-to-event data
subject to censoring. 14. Sample size estimation and power analysis:
Longitudinal data. 15. Group sequential methods, triangular methods and
stochastic curtailments. 16. Sample size re-estimation. 17. Adaptive
designs. 18. Multiple testing. 19. Subgroup analysis. 20. Competing risks.
21. Joint models for longitudinal markers and clinical outcomes. 22.
Sequential multiple assignment randomization trial (SMART) for dynamic
treatment allocation. 23. Safety data analysis. 24. Non-inferiority trials.
25. Incorporating historical data into RCTs. 26. Validation of surrogate
outcomes.