方法对比

	贝叶斯交叉制表分析	交叉分类分析
领域	统计学	统计学
方法族	Hypothesis test	Hypothesis test
起源年份	1974	1900
提出者	Gunel & Dickey	Karl Pearson
类型	Bayesian association test	Descriptive and inferential categorical analysis
开创性文献	Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557.	Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175.
别名	Bayesian chi-square test, Bayesian contingency table test, Bayes factor association test, Bayesian crosstab analysis	crosstab, contingency table analysis, two-way frequency table, bivariate frequency analysis
相关	4	5
摘要	Bayesian cross-tabulation analysis tests whether two categorical variables are associated by computing a Bayes factor that quantifies the evidence for an association model against an independence model. Unlike classical chi-square testing, it provides a continuous measure of evidence, supports the null hypothesis directly, and updates naturally with prior knowledge about the cell probabilities.	Cross-tabulation analysis (contingency table analysis) is a foundational descriptive and inferential technique for examining the relationship between two or more categorical variables. It arranges observed frequencies into a table of rows and columns, enabling visual inspection of patterns and formal chi-square testing of independence between the variables.