Statistical Thinking in Clinical Trials: Chapman & Hall/CRC Biostatistics Series
Autor Michael A. Proschanen Limba Engleză Paperback – 27 mai 2024
Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.
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Specificații
ISBN-13: 9781138058569
ISBN-10: 1138058564
Pagini: 264
Ilustrații: 84
Dimensiuni: 178 x 254 x 17 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Biostatistics Series
Locul publicării:Boca Raton, United States
ISBN-10: 1138058564
Pagini: 264
Ilustrații: 84
Dimensiuni: 178 x 254 x 17 mm
Greutate: 0.45 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Biostatistics Series
Locul publicării:Boca Raton, United States
Public țintă
Professional Practice & DevelopmentCuprins
1. Evidence and Inference. 2. 2 × 2 Tables. 3. Introduction to Clinical Trials. 4. Design of Clinical Trials. 5. Randomization/Allocation. 6. Randomization-Based Inference7 Survival Analysis. 7. Sample Size/Power. 8. Monitoring. 9. M&Ms: Multiplicity & Missing Data. 10. Adaptive Methods.
Notă biografică
Michael Proschan is a mathematical statistician and Fellow of the American Statistical Association with 32 years of clinical trial experience in cardiovascular and infectious diseases, including HIV/AIDS, Ebola virus disease, and COVID-19. He has expertise in statistical monitoring of clinical trials, having taught short courses and co-authored the book Statistical Monitoring of Clinical Trials: A Unified Approach with Gordon Lan and Janet Wittes. He co-authored, with Sally Hunsberger, one of the first papers on adaptive clinical trial methods using the observed treatment effect at an interim analysis. More recently, Dr. Proschan has written about the vital role re-randomization tests play in adaptive methods before breaking the treatment blind. He has recently been an adjunct faculty member at George Washington University and Johns Hopkins University’s Advanced Academic Programs.
Recenzii
"The goal of the book Statistical Thinking in Clinical Trials is to engender statistical intuition that can be used in different types of clinical trials, and author Michael A. Proschan brilliantly achieved the goal. The biggest part of the book is dedicated to re-randomization tests, which can be applied in a multitude of settings. The author shows their beauty and simplicity. To illustrate theoretical explanations, the author uses examples of real trials. There are not many examples of trials, but the author returns to them in different chapters and at the end of studying the book, readers become familiar with these examples. I think, it is a positive aspect of the book and provides a better understanding of the practical application of the techniques described in the book than the use of many different examples during the presentation of the material. It should be noted that author uses examples not only to show the correct methods used in trials, but also to show possible mistakes that may occur during the trial and how to avoid them. [...] I would recommend [this book] for biostatisticians who not only intent on deeper learning statistical techniques but are also interested in improvement of statistical intuition and using it in different types of clinical trials."
-Maria Ivanchuk, in ISCB News, June 2022
-Maria Ivanchuk, in ISCB News, June 2022
Descriere
The authors present the essence of statistical reasoning in clinical trials,peppered with well-known clinical trials This book uses only a small number of important principles to develop the entire statistical foundation of clinical trials.