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Logistisk regression×McNemars test×
ÄmnesområdeForskningsstatistikStatistik
FamiljProcess / pipelineHypothesis test
Ursprungsår19581947
UpphovspersonDavid Roxbee CoxQuinn McNemar
TypMethodNonparametric test for paired binary data
UrsprungskällaCox, 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 ↗
Aliaslogit model, binomial logistic regression, LRMcNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi
Närliggande35
SammanfattningLogistic 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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ScholarGateJämför metoder: Logistic Regression · McNemar's test. Hämtad 2026-06-19 från https://scholargate.app/sv/compare