Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T19:25:53.692Z Has data issue: false hasContentIssue false
  • English
  • Français

An Initial Investigation of an Australian Adaptation of the Multidimensional Aptitude Battery — II

Published online by Cambridge University Press:  29 July 2013

Kate E. Jacobs  and
Shane Costello
Kate E. Jacobs*
Affiliation:
Monash University, Australia
Shane Costello
Affiliation:
Monash University, Australia
*
Address for correspondence: Kate Jacobs, Faculty of Education, Monash University, Building 6 Wellington Road, Clayton VIC 23800, Australia. Email: kate.jacobs@monash.edu
Get access

Abstract

The Cattell-Horn-Carroll (CHC) theory of cognitive abilities has helped advance understanding regarding the relations between specific cognitive abilities and academic achievement in definite domains. However, questions over the generalisability of this research, as well the moderating effect age has on the strength of cognitive-achievement relations, means that further research is needed. This study therefore investigated the capacity for using the Multidimensional Aptitude Battery — II (MAB-II), a group-administered test of cognitive ability, to further CHC-driven research in Australia. After adapting the MAB-II verbal subtests to be suitable for use with an Australian sample, 179 adults completed the measure. Results were analaysed using both classical test and item response theory. Findings indicated that despite the MAB-II not being developed using CHC theory, the structure of the test appeared to conform to this model. Further, while an adequate number of subtests hypothesised to measure the CHC domains of Comprehension-knowledge (Gc) and Visual processing (Gv) were found to perform well psychometrically, the Arithmetic, Picture Arrangement, and Digit Symbol subtests returned questionable results. Given the advantages a group-administered test of CHC cognitive abilities would provide to CHC-driven research in Australia, suggestions for future modifications and adaptations of the test are provided.

Keywords

academic achievementassessmenteducational measurementpsychometric evaluationcognitive ability
Type
Articles
Information
The Educational and Developmental Psychologist , Volume 30 , Issue 1: Educational Psychology: Looking to the Future , July 2013 , pp. 84 - 102
Copyright
Copyright © Australian Psychological Society Ltd 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ackerman, P.L., & Lohman, D.F. (2006). Individual differences in cognitive functions. In Alexander, P.A. & Winne, P. (Eds.), Handbook of educational psychology (pp. 139–161). Mahwah, NJ: Erlbaum.Google Scholar
Barrett, P. (2005). Person-Target Profiling. In André Beauducel, Bernhard Biehl, Michael Bosniak, Wolfgang Conrad, Gisela Schönberger & Dietrich Wagener (Eds.), Multivariate research strategies: A festschrift for Werner Wittmann (pp. 63–118). Aachen, Germany: Shaker Verlag GmbH.Google Scholar
Barrett, P. (2006). Orthosim 2.01. Auckland, NZ: Author.Google Scholar
Bartlett, M. (1954). A note on the multiplying factors for various chi square approximations. Journal of the Royal Statistical Society, 16(Series B), 296–298. Retrieved from http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9868Google Scholar
Benson, N., Hulac, D.M., & Kranzler, J.H. (2010). Independent examination of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV): What does the WAIS-IV measure? Psychological Assessment, 22, 121–130. doi:10.1037/a0017767Google Scholar
Browne, M.W. (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36 (1), 111–150. doi: 10.1207/s15327906mbr3601_05Google Scholar
Cai, L. (2008). SEM of another flavour: Two new applications of the supplemented EM algorithm. British Journal of Mathematical and Statistical Psychology, 61 (2), 309–329. doi:10.1348/000711007´249603CrossRefGoogle ScholarPubMed
Cai, L., Maydeu-Olivares, A., Coffman, D., & Thissen, D. (2006). Limited-information goodness-of-fit testing of item response theory models for sparse 2P tables. British Journal of Mathematical & Statistical Psychology, 59 (1), 173–194. doi:10.1348/000711005x66419Google Scholar
Carless, S.A. (2000). The validity of score on the multidimensional aptitude battery. Educational and Psychological Measurement, 60, 592–603. doi:10.1177/00131640021970745CrossRefGoogle Scholar
Carroll, J.B. (1993). Human cognitive abilities: A survey of factor-analytic studies. New York: Cambridge University Press.CrossRefGoogle Scholar
Catell, R. (1966). The scree test for number of factors. Multivariate Behavioural Research, 1, 245–276. doi:10.1207/s15327906mbr0102_10CrossRefGoogle Scholar
Cattell, R.B. (1971). Abilities: Their structure, growth and action. Boston: Houghton Mifflin.Google Scholar
Cattell, R.B. (1982). The inheritance of personality and ability: Research methods and findings. New York: Academic Press.Google Scholar
Chen, W.-H., & Thissen, D. (1997). Local Dependence Indexes for Item Pairs Using Item Response Theory. Journal of Educational and Behavioral Statistics, 22 (3), 265–289. doi:10.3102/10769986022003265Google Scholar
Evans, J.E., Floyd, R.G., McGrew, K.S., & Leforgee, M.H. (2001). The relations between measures of Cattell-Horn-Carroll (CHC) cognitive abilities and reading achievement during childhood and adolescence. School Psychology Review, 31 (2), 246–262. Retrieved from http://www.nasponline.org/publications/spr/index-list.aspxGoogle Scholar
Fiorello, C.A., Hale, J.B., & Wycoff, K.L. (2012). Cognitive hypothesis testing: Linking test results to the real world. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 484–496). New York: Guilford Press.Google Scholar
Flanagan, D.P., Alfonso, V.C., & Ortiz, S.O. (2012). The cross-battery assessment approach: An overview, historical perspective, and current directions. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 459–483). New York: Guilford Press.Google Scholar
Flanagan, D.P., Ortiz, S.O., & Alfonso, V.C. (2007). Essentials of cross-battery assessment (2nd ed.). Hoboken, NJ: John Wiley & Sons.Google Scholar
Flanagan, D.P., Ortiz, S.O., & Alfonso, V.C. (2013). Essentials of cross-battery assessment (3rd ed.). Hoboken, NJ: John Wiley & Sons.Google Scholar
Floyd, R.G., Evans, J.J., & McGrew, K.S. (2003). Relations between measures of Cattell-Horn-Carroll (CHC) cognitive abilities and mathematics achievement across the school-age years. Psychology in the Schools, 40 (2), 155–171. doi:10.1002/pits.10083CrossRefGoogle Scholar
Floyd, R.G., Keith, T.Z., Taub, G.E., & McGrew, K.S. (2007). Cattell-Horn-Carroll cognitive abilities and their effects on reading decoding skills: g has indirect effects, more specific abilities have direct effects. School Psychology Quarterly, 22 (2), 200–233. doi:10.1037/1045-3830.22.2.200Google Scholar
Floyd, R.G., McGrew, K.S., & Evans, J.J. (2008). The relative contributions of the Cattell-Horn-Carroll cognitive abilities in explaining writing achievement during childhood and adolescence. Psychology in the Schools, 45 (2), 132–144. doi:10.1002/pits.20284CrossRefGoogle Scholar
Gignac, G.E. (2006). A confirmatory examination of the factor structure of the Multidimensional Aptitude Battery: Contrasting oblique, higher order, and nested factor models. Educational and Psychological Measurement, 66, 136–145. doi:10.1177/0013164405278568CrossRefGoogle Scholar
Gottfredson, L., & Saklofske, D.H. (2009). Intelligence: Foundations and issues in assessment. Canadian Psychology, 50, 183–195. doi:10.1037/a0016641CrossRefGoogle Scholar
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). New York: Springer.Google Scholar
Horn, J.L. (1985). Remodeling old models of intelligence. In Wolman, B.B. (Ed.), Handbook of intelligence: Theories, measurements, and applications (pp. 267–300). New York: Wiley.Google Scholar
Horn, J.L. (1986). Some thoughts about intelligence. In Sternberg, R.J. & Detterman, D.K. (Eds.), What is intelligence? Contemporary viewpoints on its nature and definition (pp. 91–96). Norwood, NJ: Ablex.Google Scholar
Horn, J.L. (1988). Thinking about human abilities. In Nesselroade, J.R. & Cattell, R.B. (Eds.), Handbook of multivariate experimental psychology (pp. 645–685). New York: Plenum Press.Google Scholar
Horn, J.L., & Blankson, A.N. (2012). Foundations for better understanding of cognitive abilities. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 73–98). New York: Guilford Press.Google Scholar
Jackson, D.N. (2003). Multidimensional Aptitude Battery-II: Technical manual. Port Huron, MI: Sigma Assessments.Google Scholar
Kaiser, H. (1970). A second generation little jiffy. Psychometrika, 35, 401–415. doi:10.1007/BF02291817Google Scholar
Kaiser, H. (1974). An index of factorial simplicity. Psychometrika, 39, 31–36. doi:10.1007/BF02291575Google Scholar
Kamphaus, R.W., Winsor, A.P., Rowe, E.W., & Kim, S. (2012). A history of intelligence test interpretation. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 56–70). New York: Guilford Press.Google Scholar
Kaplan, M., & Saccuzzo, D.P. (2013). Psychological testing: Principles, applications, & issues (8th ed., pp. 126–127). Belmont, CA: Wadsworth, Cengage Learning.Google Scholar
Keith, T.Z., & Reynolds, M.R. (2010). Cattell-Horn-Carroll abilities and cognitive tests: What we've learned from 20 years of research. Psychology in the Schools, 47, 635–650. doi:10.1002/pits.20496CrossRefGoogle Scholar
Kline, P. (2000). Handbook of psychological testing (2nd ed.). London: Routledge.Google Scholar
Kranzler, J.H. (1991). The construct validity of the multidimensional aptitude battery: A word of caution. Journal of Clinical Psychology, 47, 691–697. doi:10.1002/1097-4679(199109)47:5<691::AID-JCLP2270470510>3.0.CO;2-DGoogle Scholar
Krieshok, T.S., & Harrington, R.G. (1985). A review of the Multidimensional Aptitude Battery. Journal of Counseling and Development, 64, 87–89. doi:10.1002/j.1556-6676.1985.tb01016.xGoogle Scholar
Lee, M.S., Wallbrown, F.H., & Blaha, J. (1990). Note on the construct validity of the Multidimensional Aptitude Battery. Psychological Reports, 67, 1219–1222. doi:10.2466/PR0.67.8.1219-1222Google Scholar
Lichtenberger, E.O., & Kaufman, A.S. (2009). Essentials of WAIS-IV assessment. Hoboken, NY: John Wiley & Sons.Google Scholar
Mather, N., & Wendling, B.J. (2012). Linking cognitive abilities to academic interventions for students with learning disabilities. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 553–581). New York: Guilford Press.Google Scholar
Maydeu-Olivares, A., & Joe, H. (2005). Limited- and full-information estimation and goodness-of-fit testing in 2n contingency tables. Journal of the American Statistical Association, 100 (471), 1009–1020. doi:10.1198/016214504000002069Google Scholar
Maydeu-Olivares, A., & Joe, H. (2006). Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika, 71 (4), 713–732. doi:10.1007/s11336-005-1295-9Google Scholar
McCrae, R., Zonderman, A., Costa, P., Bond, M., & Paunonen, S. (1996). Evaluating replicability of factors in the Revised NEO Personality Inventory: Confirmatory factor analysis versus Procrustes rotation. Journal of Personality and Social Psychology, 70 (3), 552–566. doi:10.1037/0022-3514.70.3.552Google Scholar
McGrew, K.S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of giants of psychometric intelligence research. Intelligence, 37, 1–10. doi:10.1016/j.intell.2008.08.004CrossRefGoogle Scholar
McGrew, K.S. (2012). Implications of 20 years of CHC cognitive-achievement research: Back to the future and beyond CHC. Manuscript in preparation.Google Scholar
McGrew, K.S., Flanagan, D.P., Keith, T.Z., & Vanderwood, M. (1997). Beyond g: The impact of Gf-Gc specific cognitive abilities research on the future use and interpretation of intelligence tests in the schools. School Psychology Review, 26 (2), 189–210. Retrieved from http://www.nasponline.org/publications/spr/index.aspx?vol=40&issue=2Google Scholar
McGrew, K.S., & Wendling, B.J. (2010). Cattell-Horn-Carroll cognitive-achievement relations: What we have learned from the past 20 years of research. Psychology in the Schools, 47, 651–675. doi:10.1002/pits.20497Google Scholar
Miller, D.C. (2013). Essentials of school neuropsychological assessment (2nd ed.). Hoboken, NJ: Wiley & Sons.Google Scholar
Mulaik, S. (1972). The foundations of factor analysis. New York: McGraw-Hill.Google Scholar
Orlando, M., & Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24 (1), 50–64. doi:10.1177/01466216000241003Google Scholar
Orlando, M., & Thissen, D. (2003). Further investigation of the performance of S-X2: An item fit index for use with dichotomous item response theory models. Applied Psychological Measurement, 27 (4), 289–298. doi:10.1177/0146621603027004004CrossRefGoogle Scholar
Pallant, J., & Tennant, A. (2007). An introduction to the Rasch measurement model: An example using the Hospital Anxiety and Depression Scale (HADS). British Journal of Clinical Psychology, 46 (Pt 1), 1–18. doi:10.1348/014466506´96931Google Scholar
Schneider, W.J., & McGrew, K.S. (2012). The Cattell-Horn-Carroll model of intelligence. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 99–144). New York: Guilford Press.Google Scholar
Scientific Software International. (2011). IRTPRO. Lincolnwood, IL: Author.Google Scholar
ten Berge, J.M.F. (1986). Rotation to perfect congruence and the cross validation of component weights across populations. Multivariate Behavioral Research, 21 (1), 41–64. doi:10.1207/s15327906mbr2101_3Google Scholar
Thurstone, L. (1947). Multiple factor analysis. Chicago: University of Chicago Press.Google Scholar
Vellutino, F.R., Scanlon, D.M., & Lyon, R. (2000). Differentiating between difficult-to-remediate and readily remediated poor readers: More evidence against the IQ-achievement discrepancy definition of reading disability. Journal of Learning Disabilities, 33, 223–238. doi:10.1177/002221940003300302Google Scholar
Wallbrown, F.H., Carmin, C.N., & Barnett, R.W. (1988). Investigating the construct validity of the multidimensional aptitude battery. Psychological Reports, 62, 971–878. Retrieved from http://www.amsciepub.com/loi/pr0Google Scholar
Wallbrown, F.H., Carmin, C.N., & Barnett, R.W. (1989). A further note on the construct validity of the Multidimensional Aptitude Battery. Journal of Clinical Psychology, 45, 429–433. doi:10.1002/1097-4679(198905)45:3<429::AID-JCLP2270450312>3.0.CO;2-JGoogle Scholar
Watkins, M. (2000). MonteCarlo PCA for parallel analysis. State College, PA: Ed & Psych Associates.Google Scholar
Weiss, L.G., Keith, T.Z., Zhu, J., & Chen, C. (2013). WAIS-IV and clinical validation of the four- and five-factor interpretative approacjes. Journal of Psychoeducational Assessment, 31, 94–113. doi:10.1177/0734282913478030CrossRefGoogle Scholar
Widaman, K.F. (2003). Review of the Multidimensional Aptitude Battery-II. In Plake, B.S., Impara, J.C., & Spies, R.A. (Eds.), The fifteenth mental measurements yearbook (pp. 605–607). Lincoln, NE: Buros Institute of Mental Measurements.Google Scholar
Worthington, R.L., & Whittaker, T.A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34 (6), 806–838. doi:10.1177/001100000628CrossRefGoogle Scholar