方法对比

	Cramer's V	逻辑回归	麦克尼马尔检验
领域	统计学	研究统计学	统计学
方法族	Hypothesis test	Process / pipeline	Hypothesis test
起源年份	1946	1958	1947
提出者	Harald Cramér	David Roxbee Cox	Quinn McNemar
类型	Nonparametric association measure	Method	Nonparametric test for paired binary data
开创性文献	Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press. ISBN: 978-0691080420	Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242.	McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153–157.
别名	cramers v, cramer v, phi coefficient (r×c), Cramer's V (İlişki Kuvveti)	logit model, binomial logistic regression, LR	McNemar chi-square test, test for correlated proportions, paired binary test, McNemar Testi
相关	3	3	5
摘要	Cramer's V is a nonparametric effect-size statistic that measures the strength of association between two categorical variables on a scale from 0 to 1. Introduced by the Swedish mathematician Harald Cramér in his 1946 work Mathematical Methods of Statistics, it generalises the phi coefficient to tables of any size, making it the standard companion statistic to the chi-square test.	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.