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A Comparison of Matching and Weighting Methods for Causal Inference Based on Routine Health Insurance Data, or: What to do If an RCT is Impossible

Matschinger, H.; Heider, D.; König, H. · Das Gesundheitswesen · Ausgabe S 02/2020 · S. S139 bis S150

DOI 10.1055/a-1009-6634

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Autor:innenMatschinger, H.; Heider, D.; König, H.
ZeitschriftDas Gesundheitswesen
AusgabeS 02/2020
Jahrgang / SeitenJg. 82 · S. S139 bis S150

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Abstract-Vorschau

Due to a multitude of reasons Randomized Control Trials on the basis of so-called “routine data” provided by insurance companies cannot be conducted. Therefore the estimation of “causal effects” for any kind of treatment is hampered since systematic bias due to specific selection processes must be suspected. The basic problem of counterfactual, which is to evaluate the difference between two potential outcomes for t…

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Matschinger, H.; Heider, D.; König, H (2020) A Comparison of Matching and Weighting Methods for Causal Inference Based on Routine Health Insurance Data, or: What to do If an RCT is Impossible. Das Gesundheitswesen, 82 (S 02), S139 bis S150. https://doi.org/10.1055/a-1009-6634

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