Analyzing Longitudinal Clinical Trial Data
eBook - PDF

Analyzing Longitudinal Clinical Trial Data

A Practical Guide

  1. 302 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Analyzing Longitudinal Clinical Trial Data

A Practical Guide

Book details
Table of contents
Citations

About This Book

Analyzing Longitudinal Clinical Trial Data: A Practical Guide provides practical and easy to implement approaches for bringing the latest theory on analysis of longitudinal clinical trial data into routine practice.The book, with its example-oriented approach that includes numerous SAS and R code fragments, is an essential resource for statisticians and graduate students specializing in medical research.

The authors provide clear descriptions of the relevant statistical theory and illustrate practical considerations for modeling longitudinal data. Topics covered include choice of endpoint and statistical test; modeling means and the correlations between repeated measurements; accounting for covariates; modeling categorical data; model verification; methods for incomplete (missing) data that includes the latest developments in sensitivity analyses, along with approaches for and issues in choosing estimands; and means for preventing missing data. Each chapter stands alone in its coverage of a topic. The concluding chapters provide detailed advice on how to integrate these independent topics into an over-arching study development process and statistical analysis plan.

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Yes, you can access Analyzing Longitudinal Clinical Trial Data by Craig Mallinckrodt, Ilya Lipkovich in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Chapman and Hall/CRC
Year
2016
ISBN
9781351737692
Edition
1
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Acknowledgments
  8. List of Tables
  9. List of Figures
  10. List of Code Fragments
  11. Section I: Background and Setting
  12. Section II: Modeling the Observed Data
  13. Section III: Methods for Dealing with Missing Data
  14. Section IV: A Comprehensive Approach to Study Development and Analyses
  15. References
  16. Index