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Interrupted Time Series in Education Research×Propensity Score Matching×
FachgebietKausale InferenzForschungsstatistik
FamilieRegression modelProcess / pipeline
Entstehungsjahr1979-20021983
UrheberShadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization)Paul Rosenbaum and Donald Rubin
TypQuasi-experimental causal inferenceMethod
Wegweisende QuelleShadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗
AliasnamenITS in education, educational ITS, segmented regression in education, policy interrupted time seriesPSM, propensity score weighting, covariate balance
Verwandt43
ZusammenfassungInterrupted time series (ITS) analysis is a quasi-experimental design that estimates the causal effect of an education policy or intervention by examining whether an outcome trend changes abruptly at the point of implementation. Applied to education, it is used to evaluate reforms, curriculum changes, testing policies, and school interventions using routinely collected longitudinal data without a randomised control group.Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.
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ScholarGateMethoden vergleichen: Interrupted Time Series in Education Research · Propensity Score Matching. Abgerufen am 2026-06-20 von https://scholargate.app/de/compare