Propensity Score Analysis With Latent Covariates: Measurement Error Bias Correction Using the Covariate’s Posterior Mean, aka the Inclusive Factor Score

Trang Quynh Nguyen and Elizabeth A. Stuart
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Elizabeth A. Stuart: 1466Johns Hopkins Bloomberg School of Public Health

Journal of Educational and Behavioral Statistics, 2020, vol. 45, issue 5, 598-636

Abstract: We address measurement error bias in propensity score (PS) analysis due to covariates that are latent variables. In the setting where latent covariate X is measured via multiple error-prone items W , PS analysis using several proxies for X —the W items themselves, a summary score (mean/sum of the items), or the conventional factor score (i.e., predicted value of X based on the measurement model)—often results in biased estimation of the causal effect because balancing the proxy (between exposure conditions) does not balance X . We propose an improved proxy: the conditional mean of X given the combination of W , the observed covariates Z , and exposure A , denoted X WZA . The theoretical support is that balancing X WZA (e.g., via weighting or matching) implies balancing the mean of X . For a latent X , we estimate X WZA by the inclusive factor score (iFS)—predicted value of X from a structural equation model that captures the joint distribution of ( X , W , A ) given Z . Simulation shows that PS analysis using the iFS substantially improves balance on the first five moments of X and reduces bias in the estimated causal effect. Hence, within the proxy variables approach, we recommend this proxy over existing ones. We connect this proxy method to known results about valid weighting/matching functions. We illustrate the method in handling latent covariates when estimating the effect of out-of-school suspension on risk of later police arrests using National Longitudinal Study of Adolescent to Adult Health data.

Keywords: measurement error; covariate measurement error; latent variable; propensity score; factor score; inclusive factor score; bias correction; weighting function; matching function (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:45:y:2020:i:5:p:598-636

DOI: 10.3102/1076998620911920

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