方法对比
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| 贝叶斯交叉制表分析× | 贝叶斯卡方检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1974 | 1967 |
| 提出者≠ | Gunel & Dickey | I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al. |
| 类型≠ | Bayesian association test | Bayesian nonparametric association test |
| 开创性文献≠ | Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557. DOI ↗ | Good, I. J. (1967). A Bayesian significance test for multinomial distributions. Journal of the Royal Statistical Society: Series B (Methodological), 29(3), 399–418. DOI ↗ |
| 别名 | Bayesian chi-square test, Bayesian contingency table test, Bayes factor association test, Bayesian crosstab analysis | Bayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test |
| 相关≠ | 4 | 3 |
| 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. | The Bayesian chi-square test evaluates independence or goodness-of-fit in frequency tables using Bayes factors rather than classical p-values. It quantifies evidence for or against an association between categorical variables, updating prior beliefs with observed counts and delivering an odds-like ratio that distinguishes 'no evidence' from 'evidence of no effect'. |
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