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| 逻辑回归× | 麦克尼马尔检验× | |
|---|---|---|
| 领域≠ | 研究统计学 | 统计学 |
| 方法族≠ | Process / pipeline | Hypothesis test |
| 起源年份≠ | 1958 | 1947 |
| 提出者≠ | David Roxbee Cox | Quinn McNemar |
| 类型≠ | Method | Nonparametric test for paired binary data |
| 开创性文献≠ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ | McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153–157. DOI ↗ |
| 别名≠ | logit model, binomial logistic regression, LR | McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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. | McNemar's test is a nonparametric hypothesis test that compares two paired (correlated) binary proportions, such as a yes/no measurement taken on the same subjects before and after an intervention. It was introduced by Quinn McNemar in 1947 and works on the 2×2 table of matched outcomes. |
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