It is becoming increasingly important to determine whether structural models of measures of sport and activity behavior developed in North America are invarant across different populations. This study assessed (a) the cross-cultural validity of the Task and Ego Orientation in Sport Questionnaire (TEOSQ) using male college students across the United States (n = 309), Thailand (n = 312), and Taiwan (n = 307); and (b) the factorial equivalence and structured latent mean differences of the TEOSQ in these samples. Using a confirmatory factor analytic procedure, the initial test of the hypothesized two-factor structure representing task and ego orientation yielded a good fit for each sample. The factor structure was further shown to be metric invariant across the three countries. Furthermore, tests of latent means showed significant differences between groups. The United States sample exhibited the highest levels of task and ego orientation, followed by the Taiwan and Thailand samples, respectively.
Fuzhong Li, Peter Harmer, Likang Chi, and Naruepon Vongjaturapat
Chunxiao Li, Lijuan Wang, Martin E. Block, Raymond K.W. Sum, and Yandan Wu
separately for each of the two samples. Building upon the acceptable model fit of the configural model, factor loadings were constrained to be equal for the two samples to test the metric invariance. As the ΔCFI value between the configural model and metric model was smaller than .01, metric invariance
Daniel Lock, Daniel C. Funk, Jason P. Doyle, and Heath McDonald
The propensity of strongly identified fans to contribute positive organizational outcomes for sport teams underpins why team identification maintains a central position in sport management. In the current study we examine the multidimensional structure, stability, and interrelationships between the dimensions of team identification, using longitudinal data (April 2011–April 2012) collected from fans of a new Australian Rules football team (N = 602). A Confirmatory Factor Analysis (CFA) of the team identification items included (measured using the Team*ID scale), supported a five-dimensional model structure. This model was subsequently computed as a longitudinal CFA to test the configural and metric invariance of the Team*ID scale. We used a cross-lagged panel model to examine the longitudinal stability of, and interrelationships between, the dimensions: affect, behavioral involvement, cognitive awareness, private evaluation, and public evaluation. Each dimension displayed relative stability over time. In addition, public evaluation and private evaluation in April 2011 displayed a positive relationship with behavioral involvement in April 2012. Similarly, cognitive awareness in April 2011 predicted increases in public evaluation in April 2012. We conclude with implications for theory and practice.
Daniel F. Gucciardi, Chun-Qing Zhang, Vellapandian Ponnusamy, Gangyan Si, and Andreas Stenling
The aims of this study were to assess the cross-cultural invariance of athletes’ self-reports of mental toughness and to introduce and illustrate the application of approximate measurement invariance using Bayesian estimation for sport and exercise psychology scholars. Athletes from Australia (n = 353, M age = 19.13, SD = 3.27, men = 161), China (n = 254, M age = 17.82, SD = 2.28, men = 138), and Malaysia (n = 341, M age = 19.13, SD = 3.27, men = 200) provided a cross-sectional snapshot of their mental toughness. The cross-cultural invariance of the mental toughness inventory in terms of (a) the factor structure (configural invariance), (b) factor loadings (metric invariance), and (c) item intercepts (scalar invariance) was tested using an approximate measurement framework with Bayesian estimation. Results indicated that approximate metric and scalar invariance was established. From a methodological standpoint, this study demonstrated the usefulness and flexibility of Bayesian estimation for single-sample and multigroup analyses of measurement instruments. Substantively, the current findings suggest that the measurement of mental toughness requires cultural adjustments to better capture the contextually salient (emic) aspects of this concept.
Hyun-Kyoung Oh and Francis M. Kozub
The study was designed to estimate the psychometric properties of Hastings and Brown’s (2002a) Difficult Behavior Self-efficacy Scale. Participants were two samples of physical educators teaching in Korea (n = 229) and the United States (U.S.; n = 139). An initial translation of the questionnaire to Korean and pilot study were conducted along with the larger study using a confirmatory factor analysis procedure. Internal consistency estimates (weighed Omega) for the five-item scale were 0.88 both the Korean and U.S. samples. The average variances extracted for the one factor were 0.59 for the total data set and 0.57 each for the Korean and U.S. samples. Confirmatory factor analysis supported a five-item, unidimensional model for self-efficacy for the total sample: Goodness of Fit Index (GFI) = 0.97, Nonnormed Fit Index (NNFI) = 0.95, Comparative Fit Index (CFI) = 0.98, and Standardized Root Mean Square Residual (SRMR) = 0.03. Only the Root Mean Square Error of Approximation (RMSEA = 0.12) fell below criterion levels of acceptable fit, with similar fit indices occurring in separate analyses of the Korean and U.S. samples. Invariance testing across the two samples supported metric invariance (similarity of factor loadings) but not scalar invariance (U.S. means higher on all five items). The factor structure for the self-efficacy scale provides an initial estimate of validity and internal consistency for use with different teacher groups.
Ioannis Syrmpas, Athanasios Papaioannou, Nikolaos Digelidis, Gokce Erturan, and Mark Byra
(MM1) Unconstrained model (configural invariance) 1708.8 880 1.94 .040 .918 .932 (M2) Factor loadings constrained (metric invariance) 1793.2 902 1.98 .041 .914 .927 .005 (M3) Measurement intercepts (intercepts invariant) 1985.6 935 2.12 .043 .902 .913 .014 (M4) Structural covariances constrained
Graig M. Chow, Matthew D. Bird, Stinne Soendergaard, and Yanyun Yang
groups demonstrate the same factor structure, metric invariance model examines whether the factor loadings are the same across groups, and scalar invariance model further examines whether the item intercepts are the same across groups. Qualitative analysis For the open-ended responses, content analysis
Andre Koka and Heino Sildala
involved assessing the metric invariance by constraining factor loadings to be equivalent in both gender groups. The third step included evaluating the scalar invariance by constraining item intercepts, in addition to factor loadings, to be equivalent across groups. Finally, the fourth step involved
Rosemary A. Arthur, Nichola Callow, Ross Roberts, and Freya Glendinning
, relaxation, and self-talk) by testing the factor structure (configural invariance) and factor loadings (metric invariance). Method Participants We recruited athletes aged 13 years and older from sport teams/clubs and universities who received regular coaching (more at least 1 hr/week) and were actively
Rafael Burgueño, José Macarro-Moreno, Isabel Sánchez-Gallardo, María-Jesús Lirola, and Jesús Medina-Casaubón
approach proposed by Putnick and Bornstein ( 2016 ). This approach tests four successively increasingly constrained models to examine tenability of configural invariance (i.e., no equality constraints), metric invariance (i.e., equal item loadings), strong invariance (i.e., equal item loading and item