Examining Trait × Method Interactions Using Mixture Distribution Multitrait-Multimethod Models

Kaylee Litson; Christian Geiser; G. Leonard Burns; Mateu Servera

doi:10.1080/10705511.2016.1238307

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Examining Trait × Method Interactions Using Mixture Distribution Multitrait-Multimethod Models

Journal article

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Examining Trait × Method Interactions Using Mixture Distribution Multitrait-Multimethod Models

Kaylee Litson, Christian Geiser, G. Leonard Burns and Mateu Servera

Structural equation modeling, Vol.24(1), pp.31-51

01/02/2017

DOI: https://doi.org/10.1080/10705511.2016.1238307

Handle:

https://hdl.handle.net/2376/115628

PMCID: PMC5624226

PMID: 28983185

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Abstract

Multitrait-multimethod (MTMM) analyses are used in psychology to assess convergent and discriminant validity and to study method effects. Most current MTMM approaches assume that measures have equal convergent and discriminant validity across the entire range of trait values and thus do not account for potential trait × method interactions. A novel approach is presented that allows analyzing trait × method interactions using factor mixture modeling. The new MTMM mixture model allows identifying latent classes of individuals who differ with respect to convergent and discriminant validity. The new approach was applied to mother's and father's ratings of children's attention deficit hyperactivity disorder (ADHD) symptoms (N = 618). Results revealed four latent classes: one with no symptom levels, two with low symptom levels, and one with moderate symptom levels. Three classes showed evidence for convergent and discriminant validity, whereas a low symptom class lacked convergent validity for ratings of inattention. Keywords: mixture distribution, factor mixture model, convergent and discriminant validity, multitrait-multimethod analysis

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Title: Examining Trait × Method Interactions Using Mixture Distribution Multitrait-Multimethod Models
Creators: Kaylee Litson - Utah State University
Christian Geiser - Utah State University
G. Leonard Burns - Washington State University
Mateu Servera - University of the Balearic Islands
Publication Details: Structural equation modeling, Vol.24(1), pp.31-51
Academic Unit: Psychology, Department of
Publisher: Routledge
Grant note: R01 DA034770-01 / National Institute on Drug Abuse (10.13039/100000026) PSI2011-23254 / Ministry of Economy and Competitiveness Grant (Spanish Government)
Identifiers: 99900547608201842
Language: English
Resource Type: Journal article