Factorial Invariance of the ASIS Across Years

References

• American Educational Research Association, American Psychological Association & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association.
   Google Scholar
• Arslan, D., & Sak, U. (2023). Factorial invariance of the Anadolu Sak Intelligence Scale Across Gender. Journal of Psychoeducational Assessment, 41(5), 542–555. https://doi.org/10.1177/07342829231158834
   Web of Science ®Google Scholar
• Bentler, P. M. (2005). EQS 6 structural equations program manual. Multivariate Software.
   Google Scholar
• 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(3), 456–466. https://doi.org/10.1037/0033-2909.105.3.456
   Web of Science ®Google Scholar
• Chen, F. F., Sousa, K. H., & West, S. G. (2005). Testing measurement invariance of second-order factor models. Structural Equation Modeling, 12(3), 471–492. https://doi.org/10.1207/s15328007sem1203_7
   Web of Science ®Google Scholar
• Chen, H., & Zhu, J. (2008). Factor invariance between genders of the Wechsler intelligence scale for children–fourth edition. Personality and Individual Differences, 45(3), 260–266. https://doi.org/10.1016/j.paid.2008.04.008
   Web of Science ®Google Scholar
• Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5
   Web of Science ®Google Scholar
• Cırık, M., Sak, U., & Öpengin, E. (2020). An investigation of cognitive profiles of children with attention deficit hyperactivity disorder on Anadolu Sak intelligence scale. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 21(4), 1–23. https://doi.org/10.21565/ozelegitimdergisi.570505
   Google Scholar
• Daley, T. C., Whaley, S. E., Sigman, M. D., Espinosa, M. P., & Neumann, C. (2003). IQ on the rise: The Flynn effect in rural Kenyan children. Psychological Science, 14(3), 215–219. https://doi.org/10.1111/1467-9280.02434
   PubMed Web of Science ®Google Scholar
• Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Measurement and Evaluation in Counseling and Development, 43(2), 121–149. https://doi.org/10.1177/0748175610373459
   Web of Science ®Google Scholar
• Eppig, C., Fincher, C. L., & Thornhill, R. (2010). Parasite prevalence and the worldwide distribution of cognitive ability. In Proceedings of the royal society: Series B. Biological sciences (Vol. 277, pp. 3801–3808). https://doi.org/10.1098/rspb.2010.0973
   Google Scholar
• Flynn, J. R. (2006). IQ gains, WISC subtests, and fluid g: G-theory and the relevance of spearman’s hypothesis to race. In G. R. Bock, J. A. Goode, & K. Webb (Eds.), The nature of intelligence (pp. 202–227). Wiley.
   Google Scholar
• Hertzog, C., & Schaie, W. (1986). Stability and change in adult intelligence: 1. Analysis of longitudinal covariance structures. Psychology and Aging, 1(2), 159–171. https://doi.org/10.1037/0882-7974.1.2.159
   PubMedGoogle Scholar
• Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424
   Web of Science ®Google Scholar
• Immekus, J. C., & Maller, S. J. (2010). Factor structure invariance of the Kaufman adolescent and adult intelligence test across male and female samples. Educational and Psychological Measurement, 70(1), 91–104. https://doi.org/10.1177/0013164409344491
   Web of Science ®Google Scholar
• Keith, T. Z., & Reynolds, M. R. (2012). Using confirmatory factor analysis to aid in understanding the constructs measured by intelligence tests. In D. P. Flanagan & P. H. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 758–799). The Guilford Press.
   Google Scholar
• Lawrence, F. R., & Blair, C. (2003). Factorial invariance in preventive intervention: Modeling the development of intelligence in low birth weight, preterm infants. Prevention Science, 4(4), 249–261. https://doi.org/10.1023/A:1026068115471
   PubMedGoogle Scholar
• Lubke, G. H., Dolan, C. V., Kelderman, H., & Mellenbergh, G. J. (2003). On the relationship between sources of within-and between-group differences and measurement invariance in the common factor model. Intelligence, 31(6), 543–566. https://doi.org/10.1016/S0160-2896(03)00051-5
   Web of Science ®Google Scholar
• McDonald, R. P., & Ho, M. H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64–82. https://doi.org/10.1037/1082-989X.7.1.64
   PubMed Web of Science ®Google Scholar
• Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(Suppl 3), 69–77. https://doi.org/10.1097/01.mlr.0000245438.73837.89
   PubMed Web of Science ®Google Scholar
• Morgan, P. L., Frisco, M. L., Farkas, G., & Hibel, J. (2010). A propensity score matching analysis of the effects of special education services. The Journal of Special Education, 43(4), 236–254. https://doi.org/10.1177/0022466908323007
   PubMed Web of Science ®Google Scholar
• Muth´en, B., & Asparouhov, T. (2013). BSEM measurement invariance analysis: Mplus web note 17. pp. 1–48. http://www.statmodel.com/examples/webnotes/webnote17.pdf
   Google Scholar
• Muth´en, L. K., & Muth´en, B. O. (1998). Mplus user’s guide (7th ed.). Muth´en and Muth´en.
   Google Scholar
• Pietschnig, J., & Voracek, M. (2015). One century of global IQ gains: A formal meta-analysis of the Flynn effect (1909–2013). Perspectives on Psychological Science, 10(3), 282–306. https://doi.org/10.1177/1745691615577701
   Web of Science ®Google Scholar
• Reverte, I., Golay, P., Favez, N., Rossier, J., & Lecerf, T. (2015). Testing for multigroup invariance of the WISC-IV structure across France and Switzerland: Standard and CHC models. Learning and Individual Differences, 40, 127–133. https://doi.org/10.1016/j.lindif.2015.03.015
   Web of Science ®Google Scholar
• Richerson, L. P., Watkins, M. W., & Beaujean, A. A. (2014). Longitudinal invariance of the Wechsler intelligence scale for children–fourth edition in a referral sample. Journal of Psychoeducational Assessment, 32(7), 597–609. https://doi.org/10.1177/0734282914538802
   Web of Science ®Google Scholar
• Sak, U., Bal Sezerel, B., Ayas, B., Tokmak, F., Özdemir, N., Demirel Gürbüz, Ş., & Öpengin, E. (2016). Anadolu-sak intelligence scale technical and user book. Anadolu University ÜYEP Merkezi.
   Google Scholar
• Sak, U., Bal Sezerel, B., Dulger, E., Sozel, K., & Ayas, M. B. (2019). Validity of the Anadolu-Sak intelligence scale in the identification of gifted students. Psychological Test and Assessment Modeling, 61(3), 263–283.
   Google Scholar
• Schaie, K. W., Maitland, S. B., Willis, S. L., & Intrieri, R. C. (1998). Longitudinal invariance of adult psychometric ability factor structures across 7 years. Psychology and Aging, 13(1), 8–20. https://doi.org/10.1037/0882-7974.13.1.8
   PubMed Web of Science ®Google Scholar
• Scheiber, C. (2016). Is the Cattell–Horn–Carroll-Based factor structure of the Wechsler intelligence scale for children—fifth edition (WISC-V) construct invariant for a representative sample of African–American, Hispanic, and Caucasian male and female students ages 6 to 16 years? Journal of Pediatric Neuropsychology, 2, 79–88. https://doi.org/10.1007/s40817-016-0019-7
   Google Scholar
• Sözel, H. K., Öpengin, E., Sak, U., & Karabacak, F. (2018). The discriminant validity of the Anadolu-sak intelligence scale (ASIS) for gifted and other special education groups. Turkish Journal of Giftedness and Education, 8(2), 160–180.
   Google Scholar
• Tamul, Ö. F., Sezerel, B. B., Sak, U., & Karabacak, F. (2020). Social validity study of the anadolu-sak intelligence scale (ASIS). Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 49, 393–412. https://doi.org/10.9779/pauefd.575479
   Google Scholar
• 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(1), 85–89. https://doi.org/10.1037/1040-3590.16.1.85
   PubMed Web of Science ®Google Scholar
• Trahan, L. H., Stuebing, K. K., Fletcher, J. M., & Hiscock, M. (2014). The Flynn effect: A meta-analysis. Psychological Bulletin, 140(5), 1332–1360. https://doi.org/10.1037/a0037173
   PubMed Web of Science ®Google Scholar
• Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. https://doi.org/10.1177/109442810031002
   Web of Science ®Google Scholar
• Watkins, M. W., & Canivez, G. L. (2001). Longitudinal factor structure of the WISC‐III among students with disabilities. Psychology in the Schools, 38(4), 291–298. https://doi.org/10.1002/pits.1019
   Web of Science ®Google Scholar
• West, S. G., Finch, J. P., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Sage.
   Google Scholar
• Wicherts, J. M., Dolan, C. V., Hessen, D. J., Oosterveld, P., Van Baal, G. C. M., Boomsma, D. I., & Span, M. M. (2004). Are intelligence tests measurement invariant over time? Investigating the nature of the Flynn effect. Intelligence, 32(5), 509–537. https://doi.org/10.1016/j.intell.2004.07.002
   Web of Science ®Google Scholar
• Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle, & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–322). American Psychological Association.
   Google Scholar