Analysis of Observational Health Care Data Using SAS PDF

Rating: (3 reviews) Author: ISBN : 9781607642275 New from $64.02 Format: PDF

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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.

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• Product Details
• Table of Contents
• Reviews

• Perfect Paperback: 452 pages
• Publisher: SAS Institute; 1 edition (February 26, 2010)
• Language: English
• ISBN-10: 1607642271
• ISBN-13: 978-1607642275
• Product Dimensions: 10.9 x 8.3 x 1 inches
• Shipping Weight: 2.2 pounds (View shipping rates and policies)

Analysis of Observational Health Care Data Using SAS PDF

I am a masters level epidemiology/biostatistics data analyst and I took a job with a pharmaceutical company doing health claims analyses that are mostly focused on pharmacoepidemiology and health economics. I did not have any specific experience with these types of analyses and this book was a great introduction! Like another reviewer mentioned, it is focused heavily on propensity scores. Each chapter has an applied example and includes all or most of the SAS code required to do the analysis. The chapters are very focused on application and not too too much on the theoretical (as many stats books tend to be). There are sections on claims analysis and pharmacoeconomic analyses, such as cost-effectiveness and incremental net benefit analysis.

As far as the level of understanding, this book does assume a biostats and SAS foundation. I thought the authors did a great job at making the book fairly easily comprehended by a masters level biostats person like myself, even though many of these analytic methods are beyond what was explicitly covered in my coursework. I just mention this because I am sometimes unsure about the level of knowledge assumed by these books before purchasing them (you really can't tell by reading a sample of the first chapter, which is almost always extremely introductory!). I have been disappointed by some other SAS publications (eg, healthcare data analysis & SAS) that turn out to be way below my level of understanding and I don't come out with much new, useful knowledge.

GREAT, GREAT BOOK! I have already recommended it to some of my colleagues.

By anonymous

This is a great book from SAS on observational data analysis. It is great for the beginner. I highly recommend it.

By Steven Lewis