השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ANCOVA בייסיאני× | ANOVA חד-כיווני בייסיאני× | |
|---|---|---|
| תחום | סטטיסטיקה | סטטיסטיקה |
| משפחה | Hypothesis test | Hypothesis test |
| שנת המקור≠ | 2012 (formalized; Bayesian general linear models since 1960s) | 1961 (foundations); 2012 (ANOVA Bayes factors) |
| הוגה השיטה≠ | 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) |
| סוג≠ | Bayesian parametric covariate-adjusted group comparison | Bayesian hypothesis test |
| מקור מכונן≠ | 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 ↗ |
| כינויים | 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 |
| קשורות≠ | 5 | 3 |
| תקציר≠ | 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. |
| ScholarGateמערך נתונים ↗ |
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