방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 베이지안 공분산 분석 (Bayesian ANCOVA)× | 베이지안 일원 분산 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 2012 (formalized; Bayesian general linear models since 1960s) | 1961 (foundations); 2012 (ANOVA Bayes factors) |
| 창시자≠ | Building on Jeffreys (1961) and developed formally for regression/ANCOVA by Rouder & Morey (2012) | Harold Jeffreys (foundations); Jeffrey Rouder et al. (default priors for ANOVA) |
| 유형≠ | Bayesian parametric covariate-adjusted group comparison | Bayesian hypothesis test |
| 원전≠ | Rouder, J. N., & Morey, R. D. (2012). Default Bayes factors for model selection in regression. Multivariate Behavioral Research, 47(6), 877–903. DOI ↗ | Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374. DOI ↗ |
| 별칭 | Bayesian ANCOVA, Bayesian analysis of covariance, B-ANCOVA, Bayesian covariate-adjusted group comparison | Bayesian ANOVA, BF ANOVA, Bayes factor one-way ANOVA, Bayesian F-test |
| 관련≠ | 5 | 3 |
| 요약≠ | Bayesian Analysis of Covariance (Bayesian ANCOVA) extends classical ANCOVA by placing prior distributions on group effects and covariate slopes, then updating them with observed data to obtain posterior distributions and Bayes factors. It quantifies evidence for group differences on a continuous outcome after statistically adjusting for one or more continuous covariates, without relying on p-value thresholds. | Bayesian one-way ANOVA tests whether the means of three or more independent groups differ by computing a Bayes factor — a ratio that quantifies how much more likely the data are under a model that allows group differences than under the null model that assumes equal means. Unlike the classical F-test, it provides direct evidence for or against the null hypothesis rather than merely rejecting or retaining it. |
| ScholarGate데이터셋 ↗ |
|
|