Work

Incorporating Measurement Nonequivalence in a Cross-Study Latent Growth Curve Analysis

Year: 2008

Type: article

Abstract: A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement equivalence, or invariance, across the developmental periods. Similarly, when data from more than one study are combined into a single analysis, it is again important to assess measurement equivalence across the data sources. Yet, how to incorporate non-equivalence when it is discovered is not well described for applied researchers. Here, we present an item response theory approach that can be used to create scale scores from measures while explicitly accounting for non-equivalence. We demonstrate these methods in the context of a latent curve analysis in which data from two separate studies are combined to create a single longitudinal model spanning several developmental periods.

Source: Structural Equation Modeling A Multidisciplinary Journal

DOI: 10.1080/10705510802339080

Authors: David B. Flora, Patrick J. Curran, Andrea M. Hussong, Michael C. Edwards

Institutions: York University, York University, University of North Carolina at Chapel Hill, The Ohio State University

Language: English

Topic: Psychometric Methodologies and Testing

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funders: National Institute on Alcohol Abuse and Alcoholism, National Institute on Drug Abuse