This study explores the usefulness of covariates on equating test scores from nonequivalent test groups. The covariates are captured by an estimated propensity score, which is used as a proxy for latent ability to balance the test groups. The objective is to assess the sensitivity of the equated scores to various misspecifications in the…

Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…

Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…

Since Merton's classical analysis of cumulative advantage in science, it has been observed that status hierarchies display a sizable disconnect between actors' quality and rank and that they become increasingly asymmetric over time, without, however, turning into winner-take-all structures. In recent years, formal models of status hierarchies…

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…

Robustness of the school-level item response theoretic (IRT) model to violations of distributional assumptions was studied in a computer simulation. In situations where school-level precision might be acceptable for real school comparisons, expected a posteriori estimates of school ability were robust over a range of violations and conditions.…

A useful method is proposed for identifying a variable as inconsistent in factor analysis. The procedure, based on the likelihood principle, is illustrated. Statistical properties such as the effect of misspecified hypotheses, the problem of multiple comparisons, and robustness to violation of distributional assumptions are investigated. (SLD)

This study investigated the robustness of the James second-order test (James 1951; Wilcox, 1989) and the univariate F test under a two-factor fixed-effect analysis of variance (ANOVA) model in which cell variances were heterogeneous and/or distributions were nonnormal. With computer-simulated data, Type I error rates and statistical power for the…

In educational research, nonessential factors are commonly ignored and when accounted for, they are often treated statistically as fixed effects. Yet many researchers in these situations generalize their findings beyond the specific levels selected; however, the analyses may require treating the factor as a random effect. Such inappropriate…