Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Estudo de Caso-Controle Pareado× | Propensity Score Matching× | |
|---|---|---|
| Área≠ | Epidemiologia | Estatística para pesquisa |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1950s–1970s | 1983 |
| Autor original≠ | Brian MacMahon and others; systematised by Schlesselman (1982) | Paul Rosenbaum and Donald Rubin |
| Tipo≠ | Observational analytic design | Method |
| Fonte seminal≠ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755474 | 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. DOI ↗ |
| Outros nomes≠ | matched case-referent study, individually matched case-control, pair-matched case-control, matched case-control design | PSM, propensity score weighting, covariate balance |
| Relacionados≠ | 5 | 3 |
| Resumo≠ | A matched case-control study is an observational epidemiological design in which each case (a person with the disease or outcome of interest) is paired with one or more controls (persons without the outcome) who share one or more characteristics — such as age, sex, or clinical setting — to control confounding. Exposure history is then compared between cases and their matched controls to estimate the odds ratio of the exposure-disease association. | 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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