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Clinical trial data analysis using R and SAS

By: Chen, Ding-Geng (Din).
Contributor(s): Peace, Karl E [Co author] | Zhang, Pinggao [Co author].
Material type: materialTypeLabelBookSeries: Chapman & Hall/ CRC biostatistics series. Publisher: Florida CRC Press 2017Edition: 2nd.Description: xxxii, 378p. With index.ISBN: 9781498779524.Subject(s): R - Computer program language | SAS - Computer program language | Clinical trials - Statistical methodsDDC classification: 610.727 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. https://www.crcpress.com/Clinical-Trial-Data-Analysis-Using-R-and-SAS/Chen-Peace-Zhang/p/book/9781498779524
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Slot 1717 (2 Floor, East Wing) Non-fiction 610.727 C4C5 (Browse shelf) Available 199282

Table of Contents

1 Introduction to R
2 Overview of Clinical Trials
3 Treatment Comparisons in Clinical Trials
4 Treatment Comparisons in Clinical Trials with Covariates
5 Analysis of Clinical Trials with Time-to-Event Endpoints
6 Longitudinal Data Analysis for Clinical Trials
7 Sample Size Determination and Power Calculations in Clinical Trials
8 Meta-Analysis of Clinical Trials
9 Bayesian Methods in Clinical Trials
10 Bioequivalence Clinical Trials
11 Adverse Events in Clinical Trials
12 Analysis of DNA Microarrays in Clinical Trials

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.

https://www.crcpress.com/Clinical-Trial-Data-Analysis-Using-R-and-SAS/Chen-Peace-Zhang/p/book/9781498779524

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