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

Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS (EPUB ebook)

By Faries, Douglas
By Zhang, Xiang
By Kadziola, Zbigniew
By Siebert, Uwe
By Kuehne, Felicitas

Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, ...as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding
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ISBN 9781642958003
Published 15 Jan 2020
Publisher SAS Institute
Available in EPUB format
Software Adobe Ebook Compatible Devices
Language en

Full details for this title

ISBN-13 9781642958003
Stock Available
Status Wheelers ePlatform
Publisher SAS Institute
Imprint SAS Institute
Released 15 Jan 2020
Publication Country
Format EPUB ebook
Author(s) By Faries, Douglas
By Zhang, Xiang
By Kadziola, Zbigniew
By Siebert, Uwe
By Kuehne, Felicitas
Category Mathematics
Probability & Statistics
Computing and Information Technology
Number of Pages 436
Dimensions Not specified
Dewey Code Not specified
Weight Not specified - defaults to 0g
Interest Age General Audience
Reading Age General Audience

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