An Introduction to Inverse Probability Weighting and Marginal Structural Models: The Case of Environmental Tobacco Exposure and Attention Deficit/Hyperactivity Disorder Behaviors

Developmental scientists routinely examine how a focal predictor relates to some aspect of children's development. Although covariate adjustment is typically used to test hypotheses, propensity score-based methods, including inverse probability of treatment weighting (IPTW) and marginal structural models (MSM), can strengthen inference and answer more nuanced, developmentally relevant questions. This article provides a didactic introduction to IPTW and MSM methods and demonstrates their use for testing the impact of environmental smoke exposure (continuous treatment) from 6 to 90 months on parent-reported attention deficit hyperactivity disorder behaviors in first grade for 1,053 children (51% male, 44% Black) in the Family Life Project. We highlight differences that result both in conclusions and in the evaluation of assumptions for IPTW and MSM relative to more traditional covariate adjustment methods. Sample Stata syntax is provided. Public Significance Statement Covariate adjustment approaches are widely used by developmental psychologists to infer associations between focal predictors and child outcomes. Inverse probability of treatment weighting and marginal structural models are two alternative approaches, which are more widely used in public health and medicine, that provide a more sophisticated approach for addressing developmental questions. We provide a didactic orientation to these approaches through an applied example.