The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection.…

Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…

Two analyses of variance (ANOVA) models for item scores are compared. The first is an items by subject random effect ANOVA. The second is a mixed effects ANOVA with items fixed and subjects random. Comparisons regarding reliability, Cronbach's alpha coefficient, psychometric inference, and inter-item covariance structure are made between the…