HIGHLIGHTS
- who: Hiraku Kumamaru and collaborators from the Department of Healthcare Quality Assessment, Graduate School of Medicine, University of Tokyo, Tokyo have published the research work: Utility of automated data-adaptive propensity score method for confounding by indication in comparative effectiveness study in real world Medicare and registry data, in the Journal: PLOS ONE of 13/07/2021
- what: The aim of this study was to evaluate the performance of the automated data-adaptive PS approaches for confounding adjustment in a CER study with strong confounding by indication when claims data only, registry data only, and . . .
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