Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Regressão de Poisson Robusta× | Modelo Linear Generalizado (GLM)× | |
|---|---|---|
| Área | Estatística | Estatística |
| Família | Regression model | Regression model |
| Ano de origem≠ | 2004 | 1972 |
| Autor original≠ | Guangyong Zou | John A. Nelder & Robert W. M. Wedderburn |
| Tipo≠ | GLM with robust variance | Regression framework |
| Fonte seminal≠ | Zou, G. (2004). A modified Poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702-706. DOI ↗ | Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384. DOI ↗ |
| Outros nomes | modified Poisson regression, Poisson regression with robust standard errors, log-binomial alternative, sandwich-variance Poisson | GLM, generalized regression, exponential family regression, link-function model |
| Relacionados≠ | 5 | 6 |
| Resumo≠ | Robust Poisson regression fits a Poisson log-linear model to a binary outcome but replaces the model-based variance with the empirical sandwich estimator. This yields valid standard errors and risk ratios even though Poisson variance assumptions are technically violated for binary data. The approach, popularized by Zou (2004), is widely used in epidemiology as a numerically stable alternative to log-binomial regression. | The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case. |
| ScholarGateConjunto de dados ↗ |
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