A measurement model describes both the numerical and theoretical relationship between observed scores and the corresponding latent variables or constructs. Testing a measurement model across groups is required to determine if the tests scores are tapping the same constructs so that the same meaning can be ascribed to the scores. Contemporary tests of intelligence describe a number of closely related cognitive abilities, each ability being sampled by a set of observed scores. This study examined the invariance of the measurement model underlying the Wechsler Adult Intelligence Scale—IV (WAIS-IV) in the U.S. and the Canadian standardization samples. The model satisfied the assumption of invariance across samples with subtest scores reflecting similar construct measurement in both samples. Consistent with previous research with the WAIS-III, slightly higher latent variable means were found in the Canadian WAIS-IV normative sample. The results demonstrate the generality of construct validity in measurement of cognitive abilities across U.S. and Canadian samples and highlight the importance of local norms.
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. ( 1999). Standards for educational and psychological testing. Washington, DC: Authors.
2.
Bontempo, D.E., & Hofer, S.M. ( 2007). Assessing factorial invariance in cross-sectional and longitudinal studies. In A. D. Ong & M. van Dulmen (Eds.), Handbook of methods in positive psychology (pp. 153-175). New York, NY: Oxford University Press.
3.
Bowden, S.C., Cook, M.J., Bardenhagen, F.J., Shores, E.A., & Carstairs, J.R. (2004). Measurement invariance of core cognitive abilities in heterogeneous neurological and community samples . Intelligence, 33, 363-389.
4.
Bowden, S.C., Lange, R.T., Weiss, L.G., & Saklofske, D.H. (2008). Invariance of the measurement model underlying the Wechsler Adult Intelligence Scale-III in the United States and Canada. Educational and Psychological Measurement, 68, 1024-1040.
5.
Bowden, S.C., Weiss, L.G., Holdack, J.A., & Lloyd, D. ( 2006). Age-related invariance of abilities measured with the Wechsler Adults Intelligence Scale-III. Psychological Assessment , 18, 334-339.
6.
Brown, T.A. ( 2006). Confirmatory factor analysis for applied research. New York, NY: Guilford Press.
7.
Byrne, B.M., Shavelson, R.J., & Muthen, B. ( 1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456-466.
8.
Carroll, J.B. ( 1993). Human cognitive abilities. Cambridge , England: Cambridge University Press.
Cohen, J. ( 1988). Statistical power analysis for the behavioural sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
11.
Dudgeon, P.L. ( 2004). A note on extending Steiger’s (1998) multiple sample RMSEA adjustment to other noncentrality parameter-based statistics. Structural Equation Modelling, 11, 305-319.
12.
Georgas, J., Weiss, L. G., van de Vijver, F. J. R., & Saklofske, D. H. (Eds.). ( 2003). Culture and children’s intelligence: Cross-cultural analysis of the WISC-III. San Diego, CA: Academic Press.
13.
Hancock, G.R. ( 2001). Effect size, power, and sample size determination for structured means modeling and MIMIC approaches to between-groups hypothesis testing of means on a single latent construct. Psychometrika , 66, 373-388.
14.
Horn, J.L., & McArdle, J.J. ( 1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117-144.
15.
Hu, L., & Bentler, P.M. ( 1998). Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424-453.
Meredith, W. ( 1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525-543.
18.
Muthén, L.K., & Muthén, B.O. (2008). Mplus user’s guide. Version 5. Los Angeles, CA: Muthén & Muthén.
19.
Reise, S.P., Widaman, K.F., & Pugh, R.H. ( 1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114, 552-566.
20.
Rindskopf, D., & Rose, T. ( 1988). Some theory and applications for confirmatory second-order factor analysis. Multivariate Behavioural Research, 23, 51-67.
21.
Strauss M.E. ( 2001). Demonstrating specific cognitive deficits: A psychometric perspective. Journal of Abnormal Psychology, 110, 6-14.
22.
Taub, G.E., McGrew, K.S., & Witta, E.L. ( 2004). A confirmatory analysis of the factor structure and cross-age invariance of the Wechsler Adult Intelligence Scale-Third Edition. Psychological Assessment, 16, 85-89.
23.
Tulsky, D.S., & Price, L.R. ( 2003). The joint WAIS-III and WMS-III factor structure: Development and cross-validation of a six-factor model of cognitive functioning. Psychological Assessment, 15, 149-162.
24.
Vandenberg, R.J., & Lance, C.E. ( 2000). A review and synthesis of the measurements invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4-69.
25.
Widaman, K.F., & Reise, S.P. ( 1997). Exploring the measurement invariance of psychological instruments: Applications in the substance abuse domain. In K. J. Bryant & M. Windle (Eds.), The science of prevention: Methodological advance from alcohol and substance abuse research (pp. 281-324). Washington, DC: American Psychological Association .
26.
Wechsler, D. ( 1997). Wechsler Adult Intelligence Scale-Third Edition. San Antonio, TX: Psychological Corporation.
27.
Wechsler, D. ( 2003). Manual for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). San Antonio, TX: Psychological Corporation.
28.
Wechsler, D. ( 2008). Wechsler Adult Intelligence Scale-Fourth Edition. Technical and interpretive manual. San Antonio, TX: Pearson.
29.
Wechsler, D. ( 2009). Wechsler Adult Intelligence Scale-Fourth Edition, Canadian Edition. Toronto, Ontario , Canada: Pearson.
