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Propensity Score Matching with Time-Dependent Covariates

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  • Bo Lu

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  • Bo Lu, 2005. "Propensity Score Matching with Time-Dependent Covariates," Biometrics, The International Biometric Society, vol. 61(3), pages 721-728, September.
    • Handle: RePEc:bla:biomet:v:61:y:2005:i:3:p:721-728
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2005.00356.x
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    References listed on IDEAS

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    1. Kevin J. Anstrom & Anastasios A. Tsiatis, 2001. "Utilizing Propensity Scores to Estimate Causal Treatment Effects with Censored Time-Lagged Data," Biometrics, The International Biometric Society, vol. 57(4), pages 1207-1218, December.
    2. Kewei Ming & Paul R. Rosenbaum, 2000. "Substantial Gains in Bias Reduction from Matching with a Variable Number of Controls," Biometrics, The International Biometric Society, vol. 56(1), pages 118-124, March.
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    Cited by:

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    2. Sean Yiu & Li Su, 2018. "Covariate association eliminating weights: a unified weighting framework for causal effect estimation," Biometrika, Biometrika Trust, vol. 105(3), pages 709-722.
    3. Andrew J. Spieker & Emily M. Ko & Jason A. Roy & Nandita Mitra, 2020. "Nested g‐computation: a causal approach to analysis of censored medical costs in the presence of time‐varying treatment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1189-1208, November.
    4. Wenqin Pan & Donglin Zeng, 2011. "Estimating Mean Cost Using Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 67(3), pages 996-1006, September.
    5. Ronghui Xu & Yunjun Luo & Robert Glynn & Diana Johnson & Kenneth L. Jones & Christina Chambers, 2014. "Time-Dependent Propensity Score for Assessing the Effect of Vaccine Exposure on Pregnancy Outcomes through Pregnancy Exposure Cohort Studies," IJERPH, MDPI, vol. 11(3), pages 1-12, March.
    6. Kim, Seung Hoon & Park, Eun-Cheol & Jang, Suk-Yong, 2023. "Impact of long-term care insurance on medical costs and utilization by patients with Parkinson's disease," Social Science & Medicine, Elsevier, vol. 317(C).
    7. Samuel D. Pimentel & Lauren Vollmer Forrow & Jonathan Gellar & Jiaqi Li, 2020. "Optimal matching approaches in health policy evaluations under rolling enrolment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1411-1435, October.
    8. Mi Zhou & Dan Geng & Vibhanshu Abhishek & Beibei Li, 2020. "When the Bank Comes to You: Branch Network and Customer Omnichannel Banking Behavior," Information Systems Research, INFORMS, vol. 31(1), pages 176-197, March.
    9. Kevin He & Yun Li & Panduranga S. Rao & Randall S. Sung & Douglas E. Schaubel, 2020. "Prognostic score matching methods for estimating the average effect of a non-reversible binary time-dependent treatment on the survival function," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 451-470, July.
    10. Chris Schilling & Dennis Petrie & Michelle M. Dowsey & Peter F. Choong & Philip Clarke, 2017. "The Impact of Regression to the Mean on Economic Evaluation in Quasi‐Experimental Pre–Post Studies: The Example of Total Knee Replacement Using Data from the Osteoarthritis Initiative," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 35-51, December.

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