A Reproducible Workflow for Assessing Multi-Group Comparability in Short Ordinal Scales: An Applied Analytics Case Study

Cross-group comparisons require both adequate measurement-model estimation and a defensible procedure for expressing group-specific estimates on a common metric. This study presents a reproducible workflow for documenting the operational feasibility of multi-group linking in short ordinal scales. Data were collected from 373 students enrolled in Portuguese higher education who completed a 21-item entrepreneurial behaviour questionnaire comprising seven three-item dimensions. For each dimension and each of three grouping variables—gender, field of study and nationality—the workflow applied subgroup-size screening, response-category variation checks, common candidate-item screening, group-specific graded response model estimation, Stocking–Lord linking and stage-specific diagnostic reporting. All 21 group-by-dimension configurations satisfied the implemented screening rules for subgroup support, item variation and common candidate-item availability. However, operationally linked estimates were obtained for only 16 configurations. Four configurations stopped because at least one required group-specific graded response model did not converge, and one stopped because the Stocking–Lord optimisation failed. Sensitivity analyses indicated that convergent linking solutions were highly stable across numerical starting values but could change substantially when one item was removed from the three-item linking set. The resulting linked parameters and latent scores should therefore be interpreted as conditional on the fitted models, assumed common-item sets, selected reference groups and implemented estimation procedures, rather than as evidence of measurement invariance or absence of differential item functioning. The study’s principal contribution is a transparent analytical framework that distinguishes initial screening feasibility, group-specific model-estimation success and operational metric alignment, and treats subsequent cross-group contrasts solely as diagnostic illustrations of the workflow rather than as substantive findings about gender, field of study or nationality.

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Publication Details

Journal
Analytics
Published
2026-11-08
DOI
https://doi.org/10.3390/analytics5040049
Primary Topic
Psychometric Methodologies and Testing
Type
article
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article

A Reproducible Workflow for Assessing Multi-Group Comparability in Short Ordinal Scales: An Applied Analytics Case Study

Sara Nunes, María Carmen Patino-Alonso, Luis Manuel do Carmo Farinha
Analytics
Psychometric Methodologies and Testing
article

A Reproducible Workflow for Assessing Multi-Group Comparability in Short Ordinal Scales: An Applied Analytics Case Study

Sara Nunes, María Carmen Patino-Alonso, Luis Manuel do Carmo Farinha
article en

Abstract

Cross-group comparisons require both adequate measurement-model estimation and a defensible procedure for expressing group-specific estimates on a common metric. This study presents a reproducible workflow for documenting the operational feasibility of multi-group linking in short ordinal scales. Data were collected from 373 students enrolled in Portuguese higher education who completed a 21-item entrepreneurial behaviour questionnaire comprising seven three-item dimensions. For each dimension and each of three grouping variables—gender, field of study and nationality—the workflow applied subgroup-size screening, response-category variation checks, common candidate-item screening, group-specific graded response model estimation, Stocking–Lord linking and stage-specific diagnostic reporting. All 21 group-by-dimension configurations satisfied the implemented screening rules for subgroup support, item variation and common candidate-item availability. However, operationally linked estimates were obtained for only 16 configurations. Four configurations stopped because at least one required group-specific graded response model did not converge, and one stopped because the Stocking–Lord optimisation failed. Sensitivity analyses indicated that convergent linking solutions were highly stable across numerical starting values but could change substantially when one item was removed from the three-item linking set. The resulting linked parameters and latent scores should therefore be interpreted as conditional on the fitted models, assumed common-item sets, selected reference groups and implemented estimation procedures, rather than as evidence of measurement invariance or absence of differential item functioning. The study’s principal contribution is a transparent analytical framework that distinguishes initial screening feasibility, group-specific model-estimation success and operational metric alignment, and treats subsequent cross-group contrasts solely as diagnostic illustrations of the workflow rather than as substantive findings about gender, field of study or nationality.

AnalyticsVol. 5(4)
Universidade Politécnica de Castelo Branco (PT), University of Beira Interior (PT), Universidad de Salamanca (ES)
Psychometric Methodologies and Testing
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