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Journal of Causal Inference

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Covariate Balancing Inverse Probability Weights for Time-Varying Continuous Interventions

Curtis Huffman
  • Corresponding author
  • Programa Universitario de Estudios del Desarrollo, Coordinación de Humanidades, 7180 Universidad Nacional Autónoma de México, Ciudad Universitaria, Coyoacán, Mexico City, Mexico
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/ Edwin van Gameren
Published Online: 2018-04-06 | DOI: https://doi.org/10.1515/jci-2017-0002


In this paper we present a continuous extension for longitudinal analysis settings of the recently proposed Covariate Balancing Propensity Score (CBPS) methodology. While extensions of the CBPS methodology to both marginal structural models and general treatment regimes have been proposed, these extensions have been kept separately. We propose to bring them together using the generalized method of moments to estimate inverse probability weights such that after weighting the association between time-varying covariates and the treatment is minimized. A simulation analysis confirms the correlation-breaking performance of the proposed technique. As an empirical application we look at the impact the gradual roll-out of Seguro Popular, a universal health insurance program, has had on the resources available for the provision of healthcare services in Mexico.

Keywords: causal inference; covariate balancing propensity score; inverse probability weights; sequential ignorability; time-varying continuous interventions


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About the article

Received: 2017-01-13

Revised: 2018-01-24

Accepted: 2018-03-19

Published Online: 2018-04-06

Published in Print: 2018-09-25

Funding Source: Consejo Nacional de Ciencia y Tecnología

Award identifier / Grant number: CVU 173055

A preliminary version of the paper formed part of the first author’s PhD thesis, financially supported by a Consejo Nacional de Ciencia y Tecnología scholarship (CVU 173055), under the supervision of the second author. In the final phase the first author received support from the UNAM. Programa de Becas Posdoctorales en la UNAM, Becario del Programa Universitario de Estudios del Desarrollo.

Citation Information: Journal of Causal Inference, Volume 6, Issue 2, 20170002, ISSN (Online) 2193-3685, DOI: https://doi.org/10.1515/jci-2017-0002.

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