The Test of Gross Motor Development—Third Edition: A Bifactor Model, Dimensionality, and Measurement Invariance

in Journal of Motor Learning and Development

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Sedigheh Salami Department of Motor Behavior, Faculty of Sport Sciences, Alzahra University, Tehran, Iran

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Paulo Felipe Ribeiro Bandeira Department of Physical Education, Universidade Regional-URCA, Crato, Brazil
Federal University of Vale do São Francisco, Petrolina, Brazil

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Cristiano Mauro Assis Gomes Federal University of Minas Gerais, Departamento de Psicologia, Belo Horizonte, Brazil

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Parvaneh Shamsipour Dehkordi Department of Motor Behavior, Faculty of Sport Sciences, Alzahra University, Tehran, Iran

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DOI:
https://doi.org/10.1123/jmld.2020-0069
Keywords:
fundamental movement skills; motor test; psychometrics; TGMD-3
First Published Online:
22 Dec 2021
In Print:
Volume 10: Issue 1
Page Range:
116–131
Restricted access

Aim: To examine the latent structure of the Test of Gross Motor Development—Third Edition (TGMD-3) with a bifactor modeling approach. In addition, the study examines the dimensionality and model-based reliability of general and specific contributions of the test’s subscales and measurement invariance of the TGMD-3. Methods: A convenience sample of (N = 496; Mage = 7.23 ± 2.03 years; 53.8% female) typically developed children participated in this study. Three alternative measurement models were tested: (a) a unidimensional model, (b) a correlated two-factor model, and (c) a bifactor model. Results: The totality of results, including item loadings, goodness-of-fit indexes, and reliability estimates, all supported the bifactor model and strong evidence of a general factor, namely gross motor competence. Additionally, the reliability of subscale scores was poor, and it is thus contended that scoring, reporting, and interpreting of the subscales scores are probably not justifiable. Conclusions: This study shows the advantages of using bifactor approach to examine the TGMD-3 factor structure and suggests that the two traditionally hypothesized factors are better understood as “grouping” factors rather than as representative of latent constructs. In addition, our findings demonstrate that the bifactor model appears invariant for sex.

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