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| 双比例z检验× | 逻辑回归× | |
|---|---|---|
| 领域≠ | 统计学 | 研究统计学 |
| 方法族≠ | Hypothesis test | Process / pipeline |
| 起源年份≠ | 1900 | 1958 |
| 提出者≠ | Karl Pearson / classical large-sample z approximation | David Roxbee Cox |
| 类型≠ | Parametric proportion comparison | Method |
| 开创性文献≠ | Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical Methods for Rates and Proportions (3rd ed.). Wiley. DOI ↗ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ |
| 别名≠ | z-test for proportions, two-sample proportion test, one-proportion z-test, Oran Testi — z Testi (Oranlar) | logit model, binomial logistic regression, LR |
| 相关≠ | 4 | 3 |
| 摘要≠ | The proportion test (z-test for proportions) is a parametric hypothesis test that compares one or two sample proportions against a reference value or each other. Grounded in the large-sample normal approximation formalized by Fleiss, Levin, and Paik (2003), it is the standard tool for binary outcome comparisons when samples are large enough for the central limit theorem to apply. | Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science. |
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