Clinical trial data analysis with R and SAS.
Chen, Ding-Geng.
Clinical trial data analysis with R and SAS. - Second edition / Ding-Geng (Din) Chen, Karl E. Peace, Pinggao Zhang. - Chapman & Hall, 2017. - xxxii, 378 pages : illustrations ; 24 cm. - Chapman & Hall/CRC biostatistics series .
"Major updates to include SAS programs"--Preface. Previous edition: Clinical trial data analysis using R / Ding-Geng Chen, Karl E. Peace (Boca Raton, Florida : CRC Press, 2011).
Includes bibliographical references (pages 363-371) and index.
Preface.
Introduction to R.
Overview of Clinical Trials.
Sample Size Determination in Clinical Trials.
Two Treatment Comparisons in Clinical Trials.
Multi-Arm Comparisons in Clinical Trials (ANOVA).
Treatment Comparisons Incorporating Covariates in Clinical Trials (ANCOVA).
Clinical Trials with Time-to-Events Endpoints.
Clinical Trials with Repeated Measures.
Meta-Analysis in Clinical Trials.
Bayesian Methods in Clinical Trials.
Group Sequential Designs and Monitoring in Clinical Trials.
Bioequivalence Clinical Trials.
Monitoring Clinical Trials for Adverse Events.
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.
9781498779524 (hardback : alk. paper) 1498779522 (hardback : alk. paper)
Clinical trials
R (Computer program language)
SAS (Computer program language)--Statistical methods.
610.727 / CHE
Clinical trial data analysis with R and SAS. - Second edition / Ding-Geng (Din) Chen, Karl E. Peace, Pinggao Zhang. - Chapman & Hall, 2017. - xxxii, 378 pages : illustrations ; 24 cm. - Chapman & Hall/CRC biostatistics series .
"Major updates to include SAS programs"--Preface. Previous edition: Clinical trial data analysis using R / Ding-Geng Chen, Karl E. Peace (Boca Raton, Florida : CRC Press, 2011).
Includes bibliographical references (pages 363-371) and index.
Preface.
Introduction to R.
Overview of Clinical Trials.
Sample Size Determination in Clinical Trials.
Two Treatment Comparisons in Clinical Trials.
Multi-Arm Comparisons in Clinical Trials (ANOVA).
Treatment Comparisons Incorporating Covariates in Clinical Trials (ANCOVA).
Clinical Trials with Time-to-Events Endpoints.
Clinical Trials with Repeated Measures.
Meta-Analysis in Clinical Trials.
Bayesian Methods in Clinical Trials.
Group Sequential Designs and Monitoring in Clinical Trials.
Bioequivalence Clinical Trials.
Monitoring Clinical Trials for Adverse Events.
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.
9781498779524 (hardback : alk. paper) 1498779522 (hardback : alk. paper)
Clinical trials
R (Computer program language)
SAS (Computer program language)--Statistical methods.
610.727 / CHE