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Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies.

ABSTRACT: Models of confirmatory factor analysis (CFA) are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM) investigations. We show that interesting incremental information about method effects can be gained from including mean structures and tests of MI across methods in MTMM models. We present a modeling framework for testing MI in the first step of a CFA-MTMM analysis. We also discuss the relevance of MI in the context of four more complex CFA-MTMM models with method factors. We focus on three recently developed multiple-indicator CFA-MTMM models for structurally different methods [the correlated traits-correlated (methods - 1), latent difference, and latent means models; Geiser et al., 2014a; Pohl and Steyer, 2010; Pohl et al., 2008] and one model for interchangeable methods (Eid et al., 2008). We demonstrate that some of these models require or imply MI by definition for a proper interpretation of trait or method factors, whereas others do not, and explain why MI may or may not be required in each model. We show that in the model for interchangeable methods, testing for MI is critical for determining whether methods can truly be seen as interchangeable. We illustrate the theoretical issues in an empirical application to an MTMM study of attention deficit and hyperactivity disorder (ADHD) with mother, father, and teacher ratings as methods.

SUBMITTER: Geiser C

PROVIDER: S-EPMC4214357 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies.

Geiser Christian C Burns G Leonard GL Servera Mateu M

Frontiers in psychology 20141030

Models of confirmatory factor analysis (CFA) are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM) investigations. We show that interesting incremental information about method effects can be gained from including mean structures and tests of MI across methods in MTMM models. We present a modeling framework for testing MI in the first step of a CFA-MTMM analysis. We also discuss the relevance of MI ...[more]

PMID: 25400603

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Project description:Background: Distraction is a functional emotion regulation strategy utilized to relieve emotional distress. Within the attention economy perspective, distraction is increasingly associated with digital technology use, performance impairments and interference with higher-order cognitive processes. Research on smartphone distraction and its association with problematic smartphone use is still scarce and there is no available psychometric assessment tool to assess this cognitive and emotive process parsimoniously. Method: The present study reports the development and evaluation of the psychometric properties of the Smartphone Distraction Scale (SDS) through exploratory and confirmatory factor analysis, construct validity, gender invariance, and latent mean differences. The study was conducted in a sample of British university students (N = 1,001; M = 21.10 years, SD = 2.77). Results: The 16-item SDS was best conceptualized in a four-factor model solution comprising attention impulsiveness, online vigilance, emotion regulation, and multitasking. Construct validity was established using relevant psychosocial and mental health measures, with SDS scores being moderately associated with deficient self-regulation and problematic social media use. Gender measurement invariance was achieved at the configural, metric, and scalar levels, and latent mean differences indicated that females had significantly higher means than males across all four SDS latent factors. Discussion: The SDS presents with several strengths, including its theoretical grounding, relatively short length, and sound psychometric properties. The SDS enables the assessment of distraction, which appears to be one of the pathways to problematic smartphone use facilitating overuse and overreliance on smartphones for emotion regulation processes. The assessment of distraction in relation to problematic use in vulnerable populations may facilitate interventions that could encourage metacognition and benefit these groups by allowing sustained productivity in an increasingly disrupted work and social environment.

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Dataset Information

Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies.

Publications

Testing for measurement invariance and latent mean differences across methods: interesting incremental information from multitrait-multimethod studies.

Similar Datasets

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