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| 零膨胀模型× | 稳健泊松回归× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1992 | 2004 |
| 提出者≠ | Diane Lambert | Guangyong Zou |
| 类型≠ | Count regression with excess zeros | GLM with robust variance |
| 开创性文献≠ | Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗ | Zou, G. (2004). A modified Poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702-706. DOI ↗ |
| 别名 | ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial | modified Poisson regression, Poisson regression with robust standard errors, log-binomial alternative, sandwich-variance Poisson |
| 相关≠ | 6 | 5 |
| 摘要≠ | A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts. | 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. |
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