Clinical Trial Data Analysis Using R and SAS


Clinical Trial Data Analysis Using R and SAS


Georgia Southern University faculty member Karl E. Peace co-authored Clinical Trial Data Analysis Using R and SAS alongside non-faculty members Ding-Geng Chen and Pinggao Zhang.


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Book Summary: 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.

Publication Date



Chapman and Hall/CRC Press

ISBN for this edition (13-digit)


Clinical Trial Data Analysis Using R and SAS
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