Clinical Trial Data Analysis Using R and SAS (eBook)

Artikelnummer: 978-1-351-65114-1
Einband: Adobe Digital Editions
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Review of the First Edition

"The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."-Journal of Statistical Software

Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book's practical, detailed approach draws on the authors' 30 years' experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data.

What's New in the Second Edition

  • Adds SAS programs along with the R programs for clinical trial data analysis.
  • Updates all the statistical analysis with updated R packages.
  • Includes correlated data analysis with multivariate analysis of variance.
  • Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials.
  • Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.

Review of the First Edition

"The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."-Journal of Statistical Software

Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book's practical, detailed approach draws on the authors' 30 years' experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data.

What's New in the Second Edition

  • Adds SAS programs along with the R programs for clinical trial data analysis.
  • Updates all the statistical analysis with updated R packages.
  • Includes correlated data analysis with multivariate analysis of variance.
  • Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials.
  • Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.
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VerlagTaylor & Francis Ebooks
EinbandAdobe Digital Editions
Erscheinungsjahr2017
Seitenangabe410 S.
AusgabekennzeichenEnglisch
Abbildungen100 schwarz-weiße Abbildungen
Masse9'301 KB
Auflage17002 A. 2. Auflage
PlattformEPUB
AutorChen, Ding-Geng (Din) / Peace, Karl E. / Zhang, Pinggao

Über den Autor Ding-Geng (Din) Chen

Dr Ding-Geng Chen is an elected fellow of the American Statistical Association and an elected member of the International Statistical Institute. Currently he is the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University. Dr. Chen has more than 250 referred professional publications and co-authored and co-edited 42 books on clinical trial methodology, meta-analysis, data science, causal inference, and public health statistics.Dr. Jeffrey Wilson is a Professor of Statistics and Biostatistics and serves as the Associate Dean of Research and Inclusive Excellence. His research focuses on statistical analysis of binary correlated data, and he has authored numerous peer-reviewed articles in the field. He has received several prestigious honors, including the 2024 Dr. Martin Luther King Jr. Faculty.

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