Clinical Trial Data Analysis Using R and SAS
Contributors
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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Abstract
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
5-3-2017
Publisher
Chapman and Hall/CRC Press
ISBN for this edition (13-digit)
978-149-877-952-4
