Hierarchical causal variance decomposition for institution and provider comparisons in healthcare-Reference-Cited by-同舟云学术

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Hierarchical causal variance decomposition for institution and provider comparisons in healthcare

Published:2023-01-30 Issue:4 Volume:23 Page:391-415
ISSN:1387-3741
Container-title:Health Services and Outcomes Research Methodology
language:en
Short-container-title:Health Serv Outcomes Res Method

Author:

Chen Bo,McAlpine Kristen,Lawson Keith A.,Finelli Antonio,Saarela Olli

Funder

Ontario Institute for Cancer Research

Canadian Institutes of Health Research

Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health,Health Policy

Link

https://link.springer.com/content/pdf/10.1007/s10742-023-00301-6.pdf

Reference31 articles.

1. Angrist, J.D., Imbens, G.W., Rubin, D.B.: Identification of causal effects using instrumental variables. J. Am. Stat. Assoc. 91(434), 444–455 (1996)

2. Bates, D., Mächler, M., Bolker, B., Walker, S.: Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48 (2015). https://doi.org/10.18637/jss.v067.i01

3. Bell, A., Fairbrother, M., Jones, K.: Fixed and random effects models: making an informed choice. Qual. Quant. 53(2), 1051–1074 (2019)

4. Bowsher, C.G., Swain, P.S.: Identifying sources of variation and the flow of information in biochemical networks. Proc. Natl. Acad. Sci. 109(20), E1320–E1328 (2012)

5. Chen, B., Lawson, K.A., Finelli, A., Saarela, O.: Causal variance decompositions for institutional comparisons in healthcare. Stat. Methods Med. Res. 29(7), 1972–1986 (2020)

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