Measurement invariance is crucial for making valid comparisons across different groups (Kline, 2016; Vandenberg, 2002). To address the challenges associated with invariance testing such as large sample size requirements, the complexity of the model, etc., applied researchers have incorporated parcels. Parcels have been shown to alleviate skewness,…

Across many areas of psychology, concordance is commonly used to measure the (intragroup) agreement in ranking a number of items by a group of judges. Sometimes, however, the judges come from multiple groups, and in those situations, the interest is to measure the concordance between groups, under the assumption that there is some within-group…

This article illustrates the use of an explanatory item response modeling (EIRM) approach in the context of measuring group differences in science achievement. The distinction between item response models and EIRMs, recently elaborated by De Boeck and Wilson (2004), is presented within the statistical framework of generalized linear mixed models.…

This study estimates the proportion of academic and public library acquisitions in the United Kingdom for which a UK MARC record is available at the time of cataloging. A beta-binomial model is used to attribute standard errors to each estimate and to compare differences between the two types of libraries. (Author/LRW)

This study compared 4,594 student responses from three different surveys of incoming students at the University of South Florida (USF) with data from Florida's State University System (SUS) admissions files to determine what proportion of error occurs in the survey responses. Specifically, the study investigated the amount of measurement error in…

This paper explores various procedures of panel data in the estimation of causal models. The reported analyses are from the Monitoring the Future study, a nationwide questionnaire survey of 16,000 to 17,000 high school seniors conducted annually since 1975. First, the parameters of causal models are estimated in which the dependent variables are…

This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…