Analysis of Observational Health Care Data Using SAS

Nonfiction, Health & Well Being, Medical, Patient Care, Health Care Delivery, Computers, Application Software
Cover of the book Analysis of Observational Health Care Data Using SAS by Douglas E. Faries, Robert Obenchain, Josep Maria Haro, Andrew C. Leon, SAS Institute
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Author: Douglas E. Faries, Robert Obenchain, Josep Maria Haro, Andrew C. Leon ISBN: 9781607644248
Publisher: SAS Institute Publication: November 7, 2014
Imprint: SAS Institute Language: English
Author: Douglas E. Faries, Robert Obenchain, Josep Maria Haro, Andrew C. Leon
ISBN: 9781607644248
Publisher: SAS Institute
Publication: November 7, 2014
Imprint: SAS Institute
Language: English

This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.

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This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.

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