A Viable Alternative When Propensity Scores Fail: Evaluation of Inverse Propensity Weighting and Sequential G-Estimation in a Two-Wave Mediation Model

Matthew J. Valente, David P. MacKinnon, Gina L. Mazza

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Two methods from the potential outcomes framework–inverse propensity weighting (IPW) and sequential G-estimation–were evaluated and compared to linear regression for estimating the mediated effect in a two-wave design with a randomized intervention and continuous mediator and outcome. Baseline measures of the mediator and outcome can be considered confounders of the follow-up mediator–outcome relation for which adjustment is necessary to eliminate bias. To adjust for baseline measures of the mediator and outcome, IPW uses stabilized inverse propensity weights whereas sequential G-estimation uses regression adjustment. Theoretical differences between the models are described, and Monte Carlo simulations compared the performance of linear regression; IPW without weight truncation; IPW with weights truncated at the 1st/99th, 5th/95th, and 10th/90th percentiles; and sequential G-estimation. Sequential G-estimation performed similarly to linear regression, but IPW provided a biased estimate of the mediated effect, lower power, lower confidence interval coverage, and higher mean squared error. Simulation results show that IPW failed to fully adjust the follow-up mediator–outcome relation for confounding due to the baseline measures. We then compared the mediated effect estimates using data from a randomized experiment evaluating a steroid prevention program for high school athletes. Implications and future directions are discussed.

Original languageEnglish (US)
Pages (from-to)165-187
Number of pages23
JournalMultivariate Behavioral Research
Volume55
Issue number2
DOIs
StatePublished - Mar 3 2020

Keywords

  • Causal mediation
  • inverse propensity weighting
  • longitudinal mediation
  • potential outcomes framework
  • sequential G-estimation

ASJC Scopus subject areas

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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