Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS

As someone who works with observational health and education data every day, I found this book to be extremely insightful and up-to-date. If you work with similar data, have a moderate understanding of SAS, and are looking to increase the quality and accuracy of your analytic models, this book is a must-have! The authors do a fantastic job of introducing their audience to the nuances of "real world data" and the methodology of causal inference through detailed application of interesting sample data. Code and theory are set up in such a way that each chapter successfully expands on the knowledge of the one that precedes it. Cover to cover, this book is a valuable resource to any health care researcher!

Deanna Schreiber-Gregory
Independent Consultant - Statistical Theory and Data Management


Analysis of Observational Healthcare Data Using SAS®, which, as a research data analyst at a hospital, is one of my most frequently referenced books in my library. Real World Health Care Data Analysis is absolutely packed full of useful and insightful information. The table of contents may seem daunting to novice SAS users / healthcare analysts, but given the topics covered, I would recommend a brief run-through at least for anyone new to the field. For more intermediate / advanced users, this book will become a mainstay in your resource list.

Topics range from a couple of chapters on Propensity Score to Stratification for Estimating Causal Treatment Effects to what is probably one of the most important chapters for me, Evaluating the Impact of Unmeasured Confounding in Observational Research. As anyone who works as an analyst in research knows, principal investigators are sometimes hesitant to do what might take away from their research findings; confounding variables is one of them, and this book highlights why that analysis is so important. This book will be invaluable when working with researchers to build their Statistical Analysis Plans and for supporting and teaching new analysts.

I look forward to going back to this book repeatedly as I continue to build and expand my toolbox of resources and skills, and I eagerly await any future books by Faries and his co-authors.

Chris Battiston
Research Data Analyst
Women’s College Hospital

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