The concurrent and predictive validities of the Naglieri Nonverbal Ability Test (NNAT) and Raven’s Colored Progressive Matrices (CPM) were investigated in a large group of Italian third-and fifth-grade students with different sociocultural levels evaluated at the beginning and end of the school year. CPM and NNAT scores were related to math and reading comprehension tests. The CPM and NNAT concurrent and predictive validity coefficients were moderate, and there were no differences between concurrent and predictive validities with reading scores. The mutual incremental concurrent validity of the NNAT with the math test was significantly higher than the corresponding CPM validity. Finally, via step-down hierarchical regression analysis, the authors found that the predictive validity of both nonverbal tests is independent from the participants’ sociocultural level. These two relatively simple nonverbal tests are commonly used to assess general ability; however, the present study shows that they can also provide useful information for predicting the academic performance of students with different sociocultural levels.
American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author.
2.
Amoretti, G., Bazzini, L., Pesci, A., & Reggiani, M. ( 1994). Test di Matematica per la scuola dell’obbligo. Manuale [Math school achievement test. Manual.]. Florence , Italy: Organizzazioni Speciali.
3.
Anastasi, A., & Urbina, S. ( 1997). Psychological testing. Upper Saddle River, NJ: Prentice Hall.
4.
Arbisi, P.A., Ben-Porath, Y., & McNulty, J. ( 2002). A comparison of MMPI-2 validity in African American and Caucasian psychiatric inpatients. Psychological Assessment , 14, 3-15.
5.
Balboni, G., Bianchi, F., & Cubelli, R. ( 2003). Questionario sugli interessi culturali [Family Cultural Interest Scale]. Unpublished manuscript.
6.
Balboni, G., Robusto, E., Cristante, F., & Naglieri, J.A. (2009). Cultural bias in the Naglieri Nonverbal Ability Test. Manuscript in preparation.
7.
Carretti, B., Cornoldi, C., De Beni, R., & Romanò, M. (2005). Updating in working memory: A comparison of poor and good comprehenders. Journal of Experimental Child Psychology, 91, 45-66.
Cohen, J. ( 1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
10.
Cohen, J., Cohen, P., West, S.G., & Aiken, L.S. ( 2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Hillsdale, NJ: Lawrence Erlbaum.
11.
Colom, R., & Flores-Mendoza, C.E. (2007). Intelligence predicts scholastic achievement irrespective of SES factors: Evidence from Brazil. Intelligence, 35, 243-251.
12.
Cornoldi, C., & Colpo, G. ( 1998). Prove di Lettura MT per la scuola elementare-2. Manuale [MT Reading Comprehension Test-2. Manual.]. Florence, Italy: Organizzazioni Speciali.
13.
Coscarelli, A. ( 2008). Misurazione del livello socioculturale in adulti: Differenze in test di abilità logiche e linguistiche [Assessment of sociocultural level of adults: Differences in its effects in logical and linguistic tests] . Unpublished thesis, University of Aosta, Italy.
14.
Coscarelli, A., Balboni, G., & Cubelli, R. ( 2007). The problem of measuring the socio-cultural level in psychological research. In T. E. Scruggs & M. A. Mastropieri (Eds.), Advances in learning and behavioral disabilities, volume 20: International perspectives (pp. 163-181). Oxford, UK: Elsevier.
15.
Fagan, J.F. ( 2000). A theory of intelligence as processing: Implications for society. Psychology, Public Policy, and Law, 6, 168-179.
16.
Fergusson, D.M., Horwood, L.J., & Ridder, E.M. ( 2005). Show me the child at seven II: Childhood intelligence and later outcomes in adolescence and young adulthood. Journal of Child Psychology and Psychiatry, 46, 850-858.
17.
Gustafsson, J.-E., & Undheim, J.O. ( 1996). Individual differences in cognitive functions. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 186-242). New York: Prentice Hall.
18.
Hotelling, H. ( 1931). The selection of variates for use in prediction, with some comments on the general problem of nuisance parameters. Annals of Mathematical Statistics, 11, 271-283.
19.
Hunsley, J., & Mayer, G.J. ( 2003). The incremental validity of psychological testing and assessment: Conceptual, methodological, and statistical issue. Psychological Assessment, 15, 446-455.
20.
Kazlauskaite, V., & Lynn, R. ( 2002). Two-year test-retest reliability of the Coloured Progressive Matrices. Perceptual and Motor Skills, 95, 354.
21.
Jensen, A.R. ( 1998). The g factor: The science of mental ability. Westport, CT: Praeger.
22.
Johnson, W., McGue, M., & Iacono, W.G. ( 2007). Socioeconomic status and school grades: Placing their association in broader context in a sample of biological and adoptive families . Intelligence, 35, 526-541.
23.
Lamont, M., & Lareau, A. ( 1988). Cultural capital: Allusions, gaps and glissandos in recent theoretical developments. Sociological Theory, 6, 153-168.
24.
Lautenschlager, G.J., & Mendoza, J.L. ( 1986). A step-down hierarchical multiple regression analysis for examining hypotheses about test bias in prediction. Applied Psychological Measurement, 10, 133-139.
25.
Lidz, C.S., & Macrine, S.L. ( 2001). An alternative approach to the identification of gifted culturally and linguistically diverse learners. School Psychology International, 22, 74-96.
26.
Luo, D., Thompson, L.A., & Detterman, D.K. (2003). The causal factor underlying the correlation between psychometric g and scholastic performance. Intelligence, 31, 67-83.
27.
Lynn, R., & Mikk, J. (in press). National IQs predict educational attainment in math, reading and science across 56 nations. Intelligence.
28.
McCallum, R.S. ( 2003). Context for nonverbal assessment of intelligence and related abilities. In R. Steve & R. S. McCallum (Eds.), Handbook of nonverbal assessment (pp. 3-21). New York: Kluwer .
29.
Millsap, R.E. ( 2007, July). Invariance in measurement and prediction revisited . Paper presented at the 72nd annual meeting of the Psychometric Society, Tokyo.
30.
Naglieri, J.A. ( 1997). Naglieri Nonverbal Ability Test. San Antonio, TX: Psychological Corporation.
31.
Naglieri, J.A., & Bornstein, B.T. (2003). Intelligence and achievement: Just how correlated are they? Journal of Psychoeducational Assessment, 21, 244-260.
32.
Naglieri, J.A., Brulles, D., & Lansdowne, K. ( 2009). Helping gifted children learn. San Antonio, TX: Pearson.
33.
Naglieri, J.A., & Das, J.P. ( 2005). Planning, attention, simultaneous, successive (PASS) theory: A revision of the concept of intelligence. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment (2nd ed., pp. 136-182). New York: Guilford.
34.
Naglieri, J., & Ford, D.Y. ( 2003). Addressing under-representation of gifted minority children using the Naglieri Nonverbal Ability Test (NNAT). Gifted Child Quarterly, 47, 155-160.
35.
Naglieri, J.A., & Ford, D.Y. ( 2005). Increasing minority children’s participation in gifted classes using the NNAT: A response to Lohman. Gifted Child Quarterly, 49, 29-36.
36.
Naglieri, J.A., & Prewett, N.P. ( 1990). Nonverbal intelligence measures: A selected review of instruments and their use. In R. W. Kamphaus & C. R. Reynolds (Eds.), Handbook of psychological and educational assessment of children: Volume 1, intelligence and achievement (pp. 348-370). New York: Guilford.
37.
Naglieri, J.A., & Rojahn, J. ( 2004). Construct validity of the PASS theory and CAS: Correlations with achievement. Journal of Educational Psychology, 96, 174-181.
38.
Naglieri, J.A., & Ronning, M.E. ( 2000a). Comparison of White, African-American, Hispanic and Asian children on the Naglieri Nonverbal Ability Test. Psychological Assessment, 12, 328-334.
39.
Naglieri, J.A., & Ronning, M.E. ( 2000b). The relationship between general ability using the Naglieri Nonverbal Ability Test (NNAT) and Stanford Achievement Test (SAT) reading achievement. Journal of Psychoeducational Assessment, 18, 230-239.
40.
Neisser, U., Boodoo, G., Bouchard, T.J.J., Boykin, A.W., Brody, N., Ceci, S.J., et al. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77-101.
Passolunghi, M.C., & Siegel, L.S. ( 2004). Working memory and access to numerical information in children with disability in mathematics. Journal of Experimental Child Psychology, 88, 348-367.
43.
Pind, J., Gunnarsdottir, E.K., & Johannesson, H.S. (2003). Raven’s Standard Progressive Matrices: New school age norms and a study of the test’s validity. Personality and Individual Differences, 34, 375-386.
44.
Pruneti, C.A., Fenu, A., Freschi, G., Rota, S., Cocci, D., Marchionni, M., et al. (1996). Aggiornamento della standardizzazione italiana del test delle Matrici Progressive Colorate di Raven (CPM) [Update of the Italian standardization of Raven’s Colored Progressive Matrices]. Bollettino di Psicologia Applicata, 217, 51-57.
45.
Raven, J.C. ( 1984). Progressive Matrici Colore. Serie A, Ab, B. Manuale di istruzioni [Italian version Raven Progressive Matrices]. Florence, Italy: Organizzazioni Speciali.
46.
Raven, J., & Raven, J. ( 2003). Raven Progressive Matrices. In R. Steve & R. S. McCallum (Eds.), Handbook of nonverbal assessment (pp. 223-237). New York: Kluwer.
47.
Reeve, C.L., & Lam, H. ( 2005). The psychometric paradox of practice effects due to retesting: Measurement invariance and stable ability estimates in the face of observed score changes. Intelligence, 33, 535-549.
Rotundo, M., & Sackett, P.R. ( 1999). Effect of ethnic on conclusions regarding differential prediction in cognitive ability test. Journal of Applied Psychology , 84, 815-822.
50.
Rushton, J.P., Skuy, M., & Fridjhon, P. ( 2003). Performance on Raven’s Advanced Progressive Matrices by African, East Indian, and White engineering students in South Africa. Intelligence, 31, 123-137.
51.
Spinath, B., Spinath, F.M., Harlaar, N., & Plomin, R. ( 2006). Predicting school achievement from general cognitive ability, self-perceived ability, and intrinsic value. Intelligence , 34, 363-374.
52.
Steiger, J.H. ( 1980). Tests for comparing elements of a correlation matrix . Psychological Bulletin, 87, 245-251.
Teachman, J. ( 1978). Family background, educational resources and educational attainment. American Sociological Review, 52, 548-557.
55.
Tressoldi, P.E., Lonciari, I., & Vio, C. ( 2000). Treatment of specific developmental reading disorders derived from single and dual route models. Journal of Learning Disabilities, 33, 278-285.
56.
Watkins, M.W., Lei, P.-W., & Canivez, G.L. ( 2007). Psychometric intelligence and achievement: A cross-lagged panel analysis. Intelligence, 35, 59-68.
57.
Weiss, L.G., Prifitera, A., & Roid, G. ( 1993). The WISC-III and the fairness of predicting achievement across ethnic and gender groups. Journal of Psychoeducational Assessment Monograph Series: Advances in Psychoeducational Assessment, 35-42.
58.
Williams, E.S. ( 1959). The comparison of regression variables. Journal of the Royal Statistical Society, Series B, 21, 396-399.
59.
Young, J.W. ( 1994). Differential prediction of college grades by gender and ethnicity: A replication study. Educational and Psychological Measurement, 54, 1022-1029.
60.
Zucker, R. ( 1998). Issues and trends in cultural-fair assessment. Intervention in School and Clinic, 34, 103-106.
