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Life Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Biostatistics

University of Louisville

Electronic Theses and Dissertations

2014

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Statistical Methods For Assessing Treatment Effects For Observational Studies., Kristopher C. Gardner 1984- May 2014

Statistical Methods For Assessing Treatment Effects For Observational Studies., Kristopher C. Gardner 1984-

Electronic Theses and Dissertations

Though randomized clinical (RCTs) trials are the gold standard for comparing treatments, they are often infeasible or exclude clinically important subjects, or generally represent an idealized medical setting rather than real practice. Observational data provide an opportunity to study practice-based evidence, but also present challenges for analysis. Traditional statistical methods which are suitable for RCTs may be inadequate for the observational studies. In this project, four of the most popular statistical methods for observational studies: ANCOVA, propensity score matching, regression with the propensity score as a covariate, and instrumental variables (IV) are investigated through application to MarketScan insurance claims data. …