Measurement Invariance Violation Indices (MIVIs): Effect sizes for (partial) non-invariance of items and item sets

Groskurth, Katharina; Bluemke, Matthias; Lechner, Clemens M.; Raykov, Tenko

doi:10.31234/osf.io/fbshu

Cited by 2 publications

(2 citation statements)

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“…If noninvariance is detected in any phase of measurement invariance testing, the researcher should stop the analysis and determine the issues of noninvariance or accept that the constructs are noninvariant and discontinue the analysis of measurement invariance and also abandon the interpretation of group differences (Putnick & Bornstein, 2016). Another possible step may lie in an analysis of the practical effect size of such noninvariance (e.g., with dMACS effect size, see Nye et al, 2019; or with MIVI effect size, see Groskurth et al, 2021).…”

Section: Measurement Invariancementioning

confidence: 99%

“…Another possible step may lie in an analysis of the practical effect size of such noninvariance (e.g. with d MACS effect size, see Nye et al, 2019; or with MIVI effect size, see Groskurth et al, 2021). Unfortunately, in the literature there is no generally accepted consensus on what to do next when measurement invariance fails (Millsap, 2011).…”

Section: Measurement Invariancementioning

confidence: 99%

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The Necessity of Testing Measurement Invariance in Cross-Cultural Research: Potential Bias in Cross-Cultural Comparisons With Individualism– Collectivism Self-Report Scales

Lacko

Čeněk

Točík

et al. 2022

Cross-Cultural Research

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Individualism and collectivism are some of the most widely applied concepts in cultural and cross-cultural research. They are commonly applied by scholars who use arithmetic means or sum indexes of items on a scale to examine the potential similarities and differences in samples from various countries. For many reasons, cross-cultural research implicates numerous methodological and statistical pitfalls. The aim of this article is to summarize some of those pitfalls, particularly the problem of measurement non-invariance, which stems from the different understandings of questionnaire items or even different character of constructs between countries. This potential bias is reduced by latent mean comparisons performed with Multigroup Confirmatory Factor Analysis and the Measurement Invariance procedure within a Structural Equation Modeling framework. These procedures have been neglected by many researchers in the field of cross-cultural psychology, however. In this article, we compare ‘traditional’ (comparison of arithmetic means) and ‘invariant’ (latent mean comparison) approaches and provide necessary R source codes for replications of measurement invariance and latent mean comparisons within other scales. Both approaches are demonstrated with real data gathered on an Independent and Interdependent Self-Scale from 1386 participants across six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Macedonia and Albania). Our results revealed considerable differences between the ‘invariant’ and ‘traditional’ approaches, especially in post-hoc analyses. Since ‘invariant’ results can be considered less biased, this finding suggests that the currently prevalent method of comparing the arithmetic means of cross-cultural scales of individualism and collectivism can potentially cause biased results.

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Section: Measurement Invariancementioning

confidence: 99%

Section: Measurement Invariancementioning

confidence: 99%

The Necessity of Testing Measurement Invariance in Cross-Cultural Research: Potential Bias in Cross-Cultural Comparisons With Individualism– Collectivism Self-Report Scales

Lacko

Čeněk

Točík

et al. 2022

Cross-Cultural Research

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Protocol for a systematic review evaluating psychometric properties and gender-related measurement (non)invariance of self-report assessment tools for autism in adults

Uglik-Marucha,

Mason,

Belcher

et al. 2024

Syst Rev

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Background Given the recent evidence on gender differences in the presentation of autism, there is an increasing concern that current tools for autism do not adequately capture traits more often found in women. If tools for autism measure autistic traits differently based on gender alone, their validity may be compromised as they may not be measuring the same construct across genders. Measurement invariance investigations of autism measures can help assess the validity of autism constructs for different genders. The aim of this systematic review is to identify and critically appraise the psychometric properties of all self-report tools for autism in adults that meet two criteria: (a) they have been published since or included in the NICE (2014) recommendations, and (b) they have undergone gender-related measurement invariance investigations as part of their validation process. Methods A search of electronic databases will be conducted from 2014 until the present using MEDLINE, Embase, and PsycINFO using predefined search terms to identify eligible studies. The search for grey literature will include sources such as OpenGrey, APA PsycEXTRA, and Scopus. Two reviewers will independently screen titles, abstracts, and full texts for eligibility. The references of included studies will be searched for additional records. The methodological quality of the studies will be evaluated using the COSMIN Risk of Bias checklist, while psychometric quality of findings will be assessed based on criteria for good measurement properties and ConPsy checklist. The quality of the total body of evidence will be appraised using the approach outlined in the modified GRADE guidelines. Discussion This systematic review will be among the first to assess the psychometric properties and gender-related measurement invariance of self-reported measures for autism in adults that were published since (or included in) NICE (2014) guidelines. The review will provide recommendations for the most suitable tool to assess for autism without gender bias. If no such measure is found, it will identify existing tools with promising psychometric properties that require further testing, or suggest developing a new measure. Systematic review registration The protocol has been registered at the International Prospective Register of Systematic Reviews (PROSPERO). The registration number is CRD42023429350.

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Measurement Invariance Violation Indices (MIVIs): Effect sizes for (partial) non-invariance of items and item sets

Cited by 2 publications

References 13 publications

The Necessity of Testing Measurement Invariance in Cross-Cultural Research: Potential Bias in Cross-Cultural Comparisons With Individualism– Collectivism Self-Report Scales

The Necessity of Testing Measurement Invariance in Cross-Cultural Research: Potential Bias in Cross-Cultural Comparisons With Individualism– Collectivism Self-Report Scales

Protocol for a systematic review evaluating psychometric properties and gender-related measurement (non)invariance of self-report assessment tools for autism in adults

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