Original Research
Determining the dimensionality and gender invariance of the MACE work-to-family enrichment scale using bifactor and approximate invariance tests
Submitted: 25 June 2020 | Published: 28 January 2021
About the author(s)
Pieter Schaap, Department of Human Resource Management, Faculty of Economic and Management Sciences, University of Pretoria, Pretoria, South AfricaEileen Koekemoer, Department of Human Resource Management, Faculty of Economic and Management Sciences, University of Pretoria, Pretoria, South Africa
Abstract
Research purpose: The main aim of our study was to get clarity on the dimensionality of the MACE-W2FE. The secondary aim was to test for approximate invariance of the measure for gender groups.
Motivation for the study: Variations in the reported measurement models for the MACE-W2FE between studies are not conducive for theory development and called for clarification. Previous models reported were a multidimensional model and a second-order model. Approximate measurement invariance is a prerequisite for study differences between gender groups.
Research approach/design and method: We did seek to resolve the problem by using bifactor model analysis, factor strength indices and local indicator misspecification analyses using a sample of 786 South African employees. Invariance was tested using the alignment optimisation method.
Main findings: In this study, we solved a substantive research problem by determining that the data from the study best supported a single breadth factor or first-order factor model that was essentially unidimensional. The invariance tests across gender groups confirmed approximate configural, measurement and scalar invariances for the unidimensional model.
Practical/managerial implications: Researchers and practitioners may include the MACE-W2FE in studies as a single-aggregated score without negligible loss in measurement precision.
Contribution/value-add: The extended confirmatory factor analyses we conducted proved valuable in resolving the MACE-W2FE’s dimensionality vacillations, thereby enhancing the validity of inferences made from scale scores.
Keywords
Metrics
Total abstract views: 2390Total article views: 2602