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| Regresja logistyczna× | Test McNemara× | |
|---|---|---|
| Dziedzina≠ | Statystyka w badaniach | Statystyka |
| Rodzina≠ | Process / pipeline | Hypothesis test |
| Rok powstania≠ | 1958 | 1947 |
| Twórca≠ | David Roxbee Cox | Quinn McNemar |
| Typ≠ | Method | Nonparametric test for paired binary data |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy≠ | logit model, binomial logistic regression, LR | McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi |
| Pokrewne≠ | 3 | 5 |
| Podsumowanie≠ | 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. |
| ScholarGateZbiór danych ↗ |
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