Comparar métodos

	Séries Temporais Interrompidas na Pesquisa em Educação	Propensity Score Matching
Área	Inferência causal	Estatística para pesquisa
Família	Regression model	Process / pipeline
Ano de origem	1979-2002	1983
Autor original	Shadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization)	Paul Rosenbaum and Donald Rubin
Tipo	Quasi-experimental causal inference	Method
Fonte seminal	Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
Outros nomes	ITS in education, educational ITS, segmented regression in education, policy interrupted time series	PSM, propensity score weighting, covariate balance
Relacionados	4	3
Resumo	Interrupted 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.