The Impact of Partial Factorial Invariance on Cross-Group Comparisons

Assessment - Tập 26 Số 7 - Trang 1217-1233 - 2019
Dexin Shi1,2, Hairong Song1, Melanie Lewis1
1University of Oklahoma, Norman, OK USA
2University of South Carolina, Columbia, SC. USA

Tóm tắt

This study explored the impact of partial factorial invariance on cross-group comparisons of latent variables, including latent means, latent variances, structural relations (or correlations) with other constructs, and regression coefficients as predicting external variables. The results indicate that the estimates of factor mean differences are sensitive to violations of invariance on both factor loadings and intercepts. Noninvariant factor loadings were also found to influence the cross-group comparisons of factor variances and regression coefficients (slopes, in the raw metric) with external variables. However, cross-group comparisons of standardized slopes and interfactor correlations were not subject to noninvariance. Under conditions of partial invariance, we further compared the performance of four different model specification strategies. In general, fitting partially invariant models with all noninvariant parameters that were freely estimated yielded more accurate estimates of the parameters of interest. The implications of the major findings of this work, as well as recommendations and guidelines for future empirical researchers, are discussed below.

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Tài liệu tham khảo

10.1037/0033-2909.105.3.456

10.1080/10705510701301834

10.1037/a0013193

10.1177/1094428111421987

10.1016/S1068-8595(99)80006-3

10.1177/014920639902500101

Cheung G. W., 2000, Journal of Cross-Cultural Research, 31, 187

10.1207/S15328007SEM0902_5

10.1027/1614-2241.4.1.22

10.22237/jmasm/1462076700

10.1080/10705510701758349

10.1037/1040-3590.7.3.286

10.1207/S15328007SEM1004_4

10.1177/0049124198026003003

10.1080/03610739208253916

Hsieh Y.-W., 1967, The Chinese mind: Essentials of Chinese philosophy and culture, 165

10.1080/10705510903206014

10.1007/BF02291366

Lewis M. (2015). Consequences of partial factorial invariance in fitting first-order latent growth curve models (Unpublished master’s thesis). University of Oklahoma, Norman.

Li Z., 2009, Psicológica: Revista de Metodología y Psicología Experimental, 30, 343

10.1080/10705511.2011.557337

10.1177/0013164411427395

10.1207/s15327906mbr4101_4

10.1111/j.2044-8317.1971.tb00463.x

10.1207/S15328007sem1101_5

10.1037/a0027934

10.1007/BF02294825

10.1097/01.mlr.0000245438.73837.89

Millsap R. E., 2011, Statistical approaches to measurement invariance

10.1037/1082-989X.9.1.93

10.1007/BF02294365

Muthén L. K., 1998, Mplus user’s guide, 7

10.1207/S15328007SEM0904_8

10.1037/0022-006X.62.3.450

10.1080/00273171.2014.933762

R Core Team, 2015, R: A language and environment for statistical computing

10.1037/0033-2909.114.3.552

10.1177/0013164498058006010

Rosseel Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. Retrieved from http://www.jstatsoft.org/v48/i02/

10.1177/1073191110373223

10.1016/j.hrmr.2008.03.003

10.1080/00273171.2017.1306432

Song H., 2011, Asian Journal of Social Psychology, 14, 176, 10.1111/j.1467-839X.2011.01347.x

10.1037/0021-9010.91.6.1292

10.1086/209528

10.1037/1082-989X.7.2.210

10.1027/1614-2241/a000049

10.1080/17405629.2012.686740

10.1177/109442810031002

10.1016/j.adolescence.2012.10.007

10.1207/s15327906mbr2803_1

10.1037/10222-009

10.1080/10705510701301677

10.1177/0013164404264853