Work

An Empirical Assessment of the Sensitivity of Mixture Models to Changes in Measurement

Year: 2017

Type: article

Abstract: = 854) come from a laboratory analogue study of methods for creating commensurate scores of alcohol- and substance-use-related constructs when items differ systematically across participants for any given measure. Items were manipulated according to four conditions, corresponding to increasing levels of alteration to item stems, response options, or both. In Study 1, results from latent class analyses (LCA) of alcohol consequences were compared across the four conditions, revealing differences in class enumeration and configuration. In Study 2, results from factor mixture models (FMM) of alcohol expectancies were compared across two of the conditions, revealing differences in patterns and magnitude of the factor loadings and thresholds. The results suggest that even subtle differences in measurement can have substantively meaningful effects on mixture model results.

Source: Structural Equation Modeling A Multidisciplinary Journal

DOI: 10.1080/10705511.2016.1257354

Authors: Veronica T. Cole, Daniel J. Bauer, Andrea M. Hussong, Michael L. Giordano

Institution: University of North Carolina at Chapel Hill

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 Institutes of Health, National Institute on Drug Abuse

Awards: Mixture Modeling of Patterns of Substance Use: Taking into Account Measurement Bias, Harmonizing substance use and disorder measures to facilitate multistudy analyses