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Regresión Logística×La prueba de McNemar×
CampoEstadística para la investigaciónEstadística
FamiliaProcess / pipelineHypothesis test
Año de origen19581947
Autor originalDavid Roxbee CoxQuinn McNemar
TipoMethodNonparametric test for paired binary data
Fuente seminalCox, 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
Relacionados35
ResumenLogistic 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.
ScholarGateConjunto de datos
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ScholarGateComparar métodos: Logistic Regression · McNemar's test. Recuperado el 2026-06-19 de https://scholargate.app/es/compare