Regression modelQuasi-experimental / causal inference

Multi-period Propensity Score Weighting

Multi-period propensity score weighting extends the standard propensity score weighting framework to settings with repeated measurements and time-varying treatments. It constructs stabilised inverse probability weights (IPW) at each time point so that the weighted sample resembles a sequence of randomised experiments, allowing unbiased estimation of causal effects under longitudinal confounding.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Hernán, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. link
  2. Cole, S. R., & Hernán, M. A. (2008). Constructing inverse probability weights for marginal structural models. American Journal of Epidemiology, 168(6), 656-664. DOI: 10.1093/aje/kwn164

Related methods

ScholarGateMulti-period Propensity Score Weighting (Multi-period Propensity Score Weighting for Causal Inference). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/multi-period-propensity-score-weighting