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Zhao, Xin; Coxe, Stefany; Sibley, Margaret H.; Zulauf-McCurdy, Courtney; Pettit, Jeremy W. – Prevention Science, 2023
There has been increasing interest in applying integrative data analysis (IDA) to analyze data across multiple studies to increase sample size and statistical power. Measures of a construct are frequently not consistent across studies. This article provides a tutorial on the complex decisions that occur when conducting harmonization of measures…
Descriptors: Data Analysis, Sample Size, Decision Making, Test Items
Jennrich, Robert I.; Bentler, Peter M. – Psychometrika, 2012
Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…
Descriptors: Factor Structure, Factor Analysis, Models, Comparative Analysis
Reise, Steven P. – Multivariate Behavioral Research, 2012
Bifactor latent structures were introduced over 70 years ago, but only recently has bifactor modeling been rediscovered as an effective approach to modeling "construct-relevant" multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957) and highlight its…
Descriptors: Models, Factor Structure, Factor Analysis, Correlation
Jeon, Minjeong; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be…
Descriptors: Maximum Likelihood Statistics, Computation, Models, Factor Structure
Diemer, Matthew A.; Wang, Qiu; Dunkle, John H. – Journal of College Student Psychotherapy, 2009
Psychometric evaluation of presenting problem checklists is vital, given increasing clinical severity among college students. However, checklist research has focused on students at public universities and utilized inappropriate methodologies when doing so. It is unclear whether checklists used at academically selective universities reliably and…
Descriptors: Check Lists, Counseling Services, Universities, Factor Structure
Young, John W. – Educational Assessment, 2009
In this article, I specify a conceptual framework for test validity research on content assessments taken by English language learners (ELLs) in U.S. schools in grades K-12. This framework is modeled after one previously delineated by Willingham et al. (1988), which was developed to guide research on students with disabilities. In this framework…
Descriptors: Test Validity, Evaluation Research, Achievement Tests, Elementary Secondary Education

Rensvold, Rover B.; Cheung, Gordon W. – Educational and Psychological Measurement, 1998
Summarizes the problem of factorial invariance in between-group difference studies, proposes a simplified notation intended to facilitate discussion of the problem, and suggests a structured approach for testing large models. Two computer programs are offered to help with the computation. (SLD)
Descriptors: Computer Software, Factor Structure, Models
Gibbons, Robert D.; Bock, R. Darrell; Hedeker, Donald; Weiss, David J.; Segawa, Eisuke; Bhaumik, Dulal K.; Kupfer, David J.; Frank, Ellen; Grochocinski, Victoria J.; Stover, Angela – Applied Psychological Measurement, 2007
A plausible factorial structure for many types of psychological and educational tests exhibits a general factor and one or more group or method factors. This structure can be represented by a bifactor model. The bifactor structure results from the constraint that each item has a nonzero loading on the primary dimension and, at most, one of the…
Descriptors: Factor Analysis, Item Response Theory, Computation, Factor Structure
Ogot, Madara; Okudan, Gul E. – European Journal of Engineering Education, 2006
Researchers have long noted the correlation of various personality traits and team performance. Studies relating aggregate team personality traits to team performance are scattered in the literature and may not always be relevant to engineering design teams. This paper synthesizes the results from applicable Five-Factor Model (FFM)-based…
Descriptors: Personality Traits, Personality Assessment, Personality Studies, Confidentiality

Myers, Jane E.; Luecht, Richard M.; Sweeney, Thomas J. – Measurement and Evaluation in Counseling and Development, 2004
The 5-Factor Wel, the latest version of the Wellness Evaluation of Lifestyle (WEL), was examined using a completely new 3.993-person database. Through exploratory and confirmatory factor analysis with 2 discrete subsets of these data, a new 4-factor solution was identified that provided the best fit for the data and accounted for 30% of the…
Descriptors: Holistic Approach, Factor Structure, Factor Analysis, Wellness
Byrne, Barbara M. – Structural Equation Modeling, 2004
The purpose of this article is to illustrate the steps involved in testing for multigroup invariance using Amos Graphics. Based on analysis of covariance (ANCOV) structures, 2 applications are demonstrated, each of which represents a different set of circumstances. Application 1 focuses on the equivalence of a measuring instrument and tests for…
Descriptors: Statistical Analysis, Testing, Factor Structure, Adolescents
Zinbarg, Richard E.; Yovel, Iftah; Revelle, William; McDonald, Roderick P. – Applied Psychological Measurement, 2006
The extent to which a scale score generalizes to a latent variable common to all of the scale's indicators is indexed by the scale's general factor saturation. Seven techniques for estimating this parameter--omega[hierarchical] (omega[subscript h])--are compared in a series of simulated data sets. Primary comparisons were based on 160 artificial…
Descriptors: Computation, Factor Analysis, Reliability, Correlation