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This book provides practical guidance for statisticians, clinicians, and researchers involved in clinical trials in the biopharmaceutical industry, medical and public health organisations. Academics and students needing an introduction to handling missing data will also find this book invaluable.
The authors describe how missing data can affect the outcome and credibility of a clinical trial, show by examples how a clinical team can work to prevent missing data, and present the reader with approaches to address missing data effectively.
The book is illustrated throughout with realistic case studies and worked examples, and presents clear and concise guidelines to enable good planning for missing data. The authors show how to handle missing data in a way that is transparent and easy to understand for clinicians, regulators and patients. New developments are presented to improve the choice and implementation of primary and sensitivity analyses for missing data. Many SAS code examples are included – the reader is given a toolbox for implementing analyses under a variety of assumptions.
- Sales Rank: #1677300 in eBooks
- Published on: 2014-02-14
- Released on: 2014-02-14
- Format: Kindle eBook
Review
“In summary, the book is a must-have tool for any biostatistician dealing with missing data. It is an excellent reference book for postgraduate students or researchers working in the area of missing data.”� (Biometrical Journal, 1 June 2015)
“This is an excellent addition to the field, dealing with problems arising from missing data or unobserved data in clinical trials. It successfully bridges the gap between clinicians and statisticians using relatively common language to build common ground.”� �(Doody’s, 9 January 2015)
From the Back Cover
How to plan and execute a successful approach to missing data in most clinical trials.
Missing data occur in nearly all clinical trials. In order to maintain the credibility of results it is vital that measures to minimize the amount of missing data are carried out and that appropriate analysis techniques are identified and implemented correctly.The authors describe how missing data can affect the outcome and credibility of a clinical trial, show by examples how a clinical team can work to prevent missing data, and present the reader with approaches to address missing data effectively.
This book:�
- Presents clear and concise guidelines to enable good planning for missing data.
- Is illustrated throughout with realistic case studies and worked examples.
- Demonstrates how missing data can be treated in a way that is transparent and easy to understand for clinicians, regulators, and patients.
- Explores new developments in the choice and implementation of primary and sensitivity analyses for missing data.
- Includes many SAS code examples – a toolbox for implementing analyses under a variety of assumptions.
Clinical Trials with Missing Data provides practical guidance for statisticians, clinicians, and researchers involved in clinical trials in the biopharmaceutical industry, medical and public health organizations. Academics and students needing an introduction to handling missing data will also find this book invaluable.
About the Author
MICHAEL O’KELLY, Senior Strategic Biostatistics Director, Quintiles Ireland Ltd, Ireland.
BOHDANA RATITCH, Senior Biostatistician, Quintiles, Montreal, Canada.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Not great
By JH
I am not sure who this is targeted to. It is too statistically detailed for non statisticians but not detailed enough for a statistician who is trying to understand these methods at more than a surface level. It is not bad, but after reading though it I now need to get another book with a deeper review of the topic.
0 of 0 people found the following review helpful.
Excellent reference book
By ShDh
Very please with this book. Excellent reference book, particularly for Biostatisticians.
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