Clinical Trials with Missing Data: A Guide for Practitioners (Statistics in Practice) - Hardcover

Über die Autorin bzw. den Autor

MICHAEL O'KELLY, Senior Strategic Biostatistics Director, Quintiles Ireland Ltd, Ireland.

BOHDANA RATITCH, Senior Biostatistician, Quintiles, Montreal, Canada.

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Clinical Trials with Missing Data A Guide for Practitioners

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.

Aus dem Klappentext

Clinical Trials with Missing Data A Guide for Practitioners

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.