Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

Research in human development often relies on composites, that is, composed variables such as indices. Their composite nature renders these variables inaccessible to conventional factor-centric psychometric validation techniques such as confirmatory factor analysis (CFA). In the context of human development research, there is currently no…

The aim of the present research study was to compare the findings from the nonparametric MSA, DIMTEST and DETECT and the parametric dimensionality determining methods in various simulation conditions by utilizing exploratory and confirmatory methods. For this purpose, various simulation conditions were established based on number of dimensions,…

There has been some research in the use of propensity scores in the context of measurement error in the confounding variables; one recommended method is to generate estimates of the mis-measured covariate using a latent variable model, and to use those estimates (i.e., factor scores) in place of the covariate. I describe a simulation study…

Exploratory factor analysis (EFA) is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what "rotation" is, what exactly is rotating, and why we use rotation when performing…

This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.

With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables…

Supervisors evaluated counselors-in-training at multiple points during their practicum experience using the Counseling Competencies Scale (CCS; N = 1,070). The CCS evaluations were randomly split to conduct exploratory factor analysis and confirmatory factor analysis, resulting in a 2-factor model (61.5% of the variance explained).

This manuscript's purpose is to introduce Q as a methodology before providing clarification about the preferred factor analytical choices of centroid and theoretical (hand) rotation. Stephenson, the creator of Q, designated that only these choices allowed for scientific exploration of subjectivity while not violating assumptions associated with…

During the last 25 years researchers have proposed a number of conceptual frameworks to measure the various functions of instructional leadership. One of the most frequently used frameworks is the Principal Instructional Management Rating Scale (PIMRS). Despite the great number of studies employing the PIMRS, evidence for its reliability and…

Popular teamwork assessments have been strongly criticized on the grounds of poor psychometric properties and their disconnect with conceptual models of teamwork. These issues raise concerns with respect to our ability to evaluate efforts devoted to advancing teamwork in academia. We report the development of a teamwork assessment that builds on…

Challenge course programs influence a variety of psychological, social, and educational outcomes. Yet, many challenges exist when measuring challenge course outcomes like logistical constraints and a lack of specific assessment tools. This study piloted and tested an assessment tool designed for facilitators to measure participant outcomes in…

The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…

Practice and Policy: The preschool years represent a critical time to foster family engagement in education for children growing up in poverty. Yet the ways in which Latino families with lower levels of income engage with their children's education at home and at school might look different from how middle-income parents from the dominant U.S.…