Psychometric properties of a brief non-verbal test of g factor intelligence

(1) * Luis Anunciação Mail (Pontifical Catholic University of Rio de Janeiro, Brazil)
(2) Louise Marques Mail (Pontifical Catholic University of Rio de Janeiro, Brazil)
(3) Christopher Murray Mail (Center on Human Development, University of Oregon, United States)
(4) Anna C Portugal Mail (Pontifical Catholic University of Rio de Janeiro, Brazil)
(5) Ivan Rabelo Mail (Universidade Paulista, Brazil)
(6) Jesus Landeira-Fernandez Mail (Pontifical Catholic University of Rio de Janeiro, Brazil)
(7) Roberto Cruz Mail (Federal University of Santa Catarina, Brazil)
*corresponding author


Intelligence is the most studied construct in psychology and cognitive neuroscience. In Brazil, the administration of intelligence tests is needed for a number of social rights, including driving privileges. Such requirements have led to a large testing industry but the vast majority of intelligence tests require extended administration times and language skills. In this study, we sought to investigate the psychometric properties and normative results of a new non-verbal intelligence test, the General Matrix of Intelligence (GMI). The GMI is comprised of 28 matrix-based items and can be administered in as little as six-minutes. In this initial pilot test, the GMI was administered to 1,326 participants, ages 15-64 years old (M = 25.65 years, SD = 9.6 years), from all regions in Brazil. These data were analyzed using a 2PL Item Response Theory model, regression analyses were conducted to determine the role of sociodemographic factors, and preliminary norms were computed. Results indicated a unidimensional solution that reproduced the g factor theory, invariance across genders, evidence that cognitively demanding items involving movement or three-dimensional shapes were more difficult than items with less cognitive load, a normal distribution for results, and an interaction between education level and age group in predicting performance. Implications of these findings for research and practice are discussed and all data and codes are provided at


g factor; general intelligence; invariance; intelligence assessment; psychometrics; Brazil



Article metrics

10.47679/jopp.617532024 Abstract views : 98 | PDF views : 56




Full Text



Anderson, J. R. (1990). Cognitive psychology and its implications (3rd ed.). W H Freeman; Times Books; Henry Holt & Co.

Alves, I. C. B., & Oliveira, M. S. (2017). Avaliação psicológica para motoristas profissionais: Fatores psicossociais e o teste psicológico como instrumento de intervenção [Psychological assessment for professional drivers: Psychosocial factors and psychological testing as an intervention tool]. Psicologia: Teoria e Prática, 19(1), 139-151.

Anastasi, A., & Urbina, S. (1997). Psychological testing (7th ed.). Prentice Hall/Pearson Education.

Anstey, K. J., Windsor, T. D., Luszcz, M. A., & Andrews, G. R. (2006). Predicting Driving Cessation over 5 Years in Older Adults: Psychological Well-Being and Cognitive Competence Are Stronger Predictors than Physical Health. Journal of the American Geriatrics Society, 54(1), 121–126.

‌ Anstey, K. J., Wood, J., Caldwell, H., Kerr, G., & Lord, S. R. (2009). Comparison of Self-Reported Crashes, State Crash Records and an On-Road Driving Assessment in a Population-Based Sample of Drivers Aged 69-95 Years. Traffic Injury Prevention, 10(1), 84–90.

Anunciação, L., Portugal, A. C., & Landeira-Fernandez, J. (2021). Neuropsychological assessment: Statistical aspects of the relationship between percentile and classification. Interação Em Psicologia, 25(3).

Anunciação, L., Portugal, A., Rabelo, I., & Landeira-Fernandez, J. (2021). Non-verbal intelligence outperforms selective attention in a visual short-term memory test. Psicologia: Reflexão e Crítica, 34(1), 35.

Baker, F. B., & Kim, S. H. (2017). The basics of item response theory using R. Springer.

Bünger, A., Grieder, S., Schweizer, F., & Grob, A. (2021). The comparability of intelligence test results: Group- and individual-level comparisons of seven intelligence tests. Journal of School Psychology, 88, 101–117.

Burns, E. (1988). Normalized standard score spreadsheet and norm table generator. Journal of School Psychology.

Caird, J. K., Johnston, K. A., Willness, C. R., Asbridge, M., & Steel, P. (2014). A meta-analysis of the effects of texting on driving. Accident Analysis & Prevention, 71, 311–318.

Carroll, J. B. (2003). The Higher-stratum Structure of Cognitive Abilities. The Scientific Study of General Intelligence pp. 5–21. Elsevier.

Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1–22.

Chalmers, R. P. (2012). mirt : A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6).

Chen, F. F. (2007). Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464–504.

Ciotta, S., Cruz, R. M., & Dagostin, C. G.. (2021). Avaliação psicológica de condutores no trânsito no Brasil: marcos históricos e desafios atuais. Revista Plural, 1(3)

Colom, R., Karama, S., Jung, R. E., & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in Clinical Neuroscience, 12(4), 489–501.

Condon, D. M., & Revelle, W. (2014). The international cognitive ability resource: Development and initial validation of a public-domain measure. Intelligence, 43, 52–64.

Contran. (2022). Resolução nº 927, de 28 de março de 2022

Conway, A. R. A., Kovacs, K., Hao, H., Rosales, K. P., & Snijder, J.-P. (2021). Individual Differences in Attention and Intelligence: A United Cognitive/Psychometric Approach. Journal of Intelligence, 9(3), 34.

Cramer, Y. (2021). Distribution across Age of Raw and Scaled Intelligence Scores - the DARSIS model. PsyArXiv (OSF Preprints).

Das, J. P., Naglieri, J. A., & Kirby, J. R. (1994). Assessment of cognitive processes: The PASS theory of intelligence. Allyn & Bacon.

Deary, I. J. (2012). Intelligence. Annual Review of Psychology, 63(1), 453–482.

Detterman, D. (2014). Editor’s note. Intelligence, 42, 135.

Flanagan JE, Landa R, Bhat A, et al. (2012) Head lag in infants at risk for autism: a preliminary study. American Journal of Occupational Therapy, 66(5): 577–585

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689-707.

Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. Basic Books.

Goleman, D. (1995). Emotional Intelligence: Why it can Matter More that IQ. New York: Bantam.

Gottfredson, L. S. (1997). Why g matters: The complexity of everyday life. Intelligence, 24(1), 79–132.

Gottfredson, L., & Saklofske, D. H. (2009). Intelligence: Foundations and issues in assessment. Canadian Psychology / Psychologie Canadienne, 50(3), 183–195.

Guilmette, T. J., Sweet, J. J., Hebben, N., Koltai, D., Mahone, E. M., Spiegler, B. J., Stucky, K., & Westerveld, M. (2020). American Academy of Clinical Neuropsychology consensus conference statement on uniform labeling of performance test scores. The Clinical Neuropsychologist, 34(3), 437–453.

Halpern. D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S., & Gernsbacher, M. A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest 8(1):1-51.

Hambleton, R. K., Merenda, P. F., & Spielberger, C. D. (2005). Adapting educational and psychological tests for cross-cultural assessment. Lawrence Erlbaum Associates.

Heckman, J. J. (2006). Skill formation and the economics of investing in disadvantaged children. Science, 312(5782), 1900–1902.

Herrnstein, R. J., & Murray, C. (2010). The bell curve: Intelligence and class structure in American life. Simon and Schuster.

Horn, J. L., & McArdle, J. J. (2007). Understanding human intelligence since Spearman. In R. Cudeck & R. C. MacCallum (Eds.), Factor analysis at 100: Historical developments and future directions (pp. 205–247). Lawrence Erlbaum Associates Publishers.

Hutter, F., Kotthoff, L., & Vanschoren, J. (Eds.). (2015). Automatic machine learning: methods, systems, challenges. Springer.

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.

Jensen, A. R. (1998). The g factor: The science of mental ability. Praeger Publishers; Greenwood Publishing Group.

Johnson, W., Bouchard, T. J., Krueger, R. F., McGue, M., & Gottesman, I. I. (2004). Just one g: Consistent results from three test batteries. Intelligence, 32(1), 95–107.

Kaufman, A. S., & Kaufman, N. L. (2004). Kaufman assessment battery for children: Second edition (KABC-II). Circle Pines, MN: American Guidance Service.

Keith, T. Z., Reynolds, M. R., Roberts, L. G., Winter, A. L., & Austin, C. A. (2011). Sex differences in latent cognitive abilities ages 5 to 17: Evidence from the Differential Ability Scales—Second Edition. Intelligence, 39(5), 389–404.

Kievit, R. A., Fuhrmann, D., Borgeest, G. S., Simpson-Kent, I. L., & Henson, R. N. A. (2018). The neural determinants of age-related changes in fluid intelligence: A pre-registered, longitudinal analysis in UK Biobank. Wellcome Open Research, 3, 38.

Koch, M., Becker, N., Spinath, F. M., & Greiff, S. (2021). Assessing intelligence without intelligence tests. Future perspectives. Intelligence, 89, 101596.

Lacko, D., Čeněk, J., Točík, J., Avsec, A., Đorđević, V., Genc, A., Haka, F., Šakotić-Kurbalija, J., Mohorić, T., Neziri, I., & Subotić, S. (2022). The necessity of testing measurement invariance in cross-cultural research: Potential bias in cross-cultural comparisons with individualism– Collectivism self-report scales. Cross-Cultural Research, 56(2–3), 228–267.

Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne M. (2009). Social science.Computational social science. Science. 6;323(5915):721-3.

Le Carret, N., Lafont, S., Letenneur, L., Dartigues, J.-F., Mayo, W., & Fabrigoule, C. (2003). The effect of education on cognitive performances and its implication for the constitution of the cognitive reserve. Developmental Neuropsychology, 23(3), 317–337.

Lúcio, P. S., Cogo-Moreira, H., Puglisi, M., Polanczyk, G. V., & Little, T. D. (2019). Psychometric investigation of the raven’s colored progressive matrices test in a sample of preschool children. Assessment, 26(7), 1399–1408.

Matarazzo, J. D. (1990). Psychological assessment versus psychological testing: Validation from Binet to the school, college, and adult intelligence tests. American Psychologist, 45(9), 999-1017.

Mayer, J. D., Roberts, R. D., & Barsade, S. G. (2008). Human Abilities: Emotional Intelligence. Annual Review of Psychology, 59(1), 507–536.

McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37(1), 1–10.

Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci, S. J., Halpern, D. F., Loehlin, J. C., Perloff, R., Sternberg, R. J., & Urbina, S. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51(2), 77–101.

Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012). Intelligence: New findings and theoretical developments. Am Psychol. 67(2):130-59.

Nyberg, L., Lövdén, M., Riklund, K., Lindenberger, U., & Bäckman, L. (2012). Memory aging and brain maintenance. Trends in Cognitive Sciences, 16(5), 292–305.

Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kan, E., Kuperman, J. M., Akshoomoff, N., Amaral, D. G., Bloss, C. S., Libiger, O., Schork, N. J., Murray, S. S., Casey, B. J., Chang, L., Ernst, T. M., Frazier, J. A., Gruen, J. R., Kennedy, D. N., Van Zijl, P., & Mostofsky, S. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18(5), 773–778.

Parsons, T. D., & Rizzo, A. A. (2008). Affective outcomes of virtual reality exposure

therapy for anxiety and specific phobias: A meta-analysis. Journal of Behavior Therapy and Experimental Psychiatry, 39(3), 250–261.

Palejwala, M. H., & Fine, J. G. (2015). Gender differences in latent cognitive abilities in

children aged 2 to 7. Intelligence, 48, 96–108.

Plomin, R., & Deary, I. (2015). Genetics and intelligence differences: Five special findings. Molecular Psychiatry, 20 (1), 98–108.

Redvaldsen, D. (2020). Do the Mega and Titan tests yield accurate results? An investigation into two experimental intelligence tests. Psych, 2(2), 97–113.

Reynolds, C. R., & Kamphaus, R. W. (2003). Handbook of psychological assessment (4th ed.). Wiley.

Reynolds, C. R., & Keith, T. Z. (2013). The future of assessment in psychology: predicting, explaining, and preventing behavior problems. Routledge.

Rindermann, H., Becker, D., & Coyle, T. R. (2020). Survey of expert opinion on intelligence: Intelligence research, experts’ background, controversial issues, and the media. Intelligence, 78, 101406.

Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological Science, 29(8), 1358–1369.

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36.

Rosseti, M. O., Rabelo, I. S. A., Leme, I. F. A. de S., Pacanaro, S. V., & Güntert, I. B. (2009). Evidências de validade das Matrizes Progressivas Avançadas de Raven em universitários. Psico-USF, 14(2), 177–184.

Sattler, J. M. (2008). Assessment of children: Cognitive foundations (5th ed.). Jerome M. Sattler, Publisher, Inc.

Salthouse, T. A. (2009). When does age-related cognitive decline begin? Neurobiol Aging, 30(4):507-14.

Schaie, K. W. (2013). Developmental influences on adult intelligence: The Seattle Longitudinal Study (2nd ed.). Oxford University Press.

Schmidt, F. L., & Hunter, J. (2004). General mental ability in the world of work: Occupational attainment and job performance. Journal of Personality and Social Psychology, 86(1), 162–173.

Silva, F. H. V. C. , & Günther, H. (2009). Psicologia do trânsito no Brasil: de onde veio e para onde caminha?. Temas em Psicologia, 17(1), 163-175.

Spearman, C. (1904). “General Intelligence,” Objectively Determined and Measured. The American Journal of Psychology.

Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.

Sternberg, R. J., & Grigorenko, E. L. (2002). The theory of successful intelligence as a basis for instruction and assessment. ASCD.

Sternberg, R. J. (2017). Wisdom, intelligence, and creativity synthesized. Cambridge University Press.

Sternberg, R. J. (2018a). Theories of intelligence. APA Handbook of Giftedness and Talent, 145–161. American Psychological Association.

Sternberg, R. J. (2018b). Applying intelligence to the workplace. Routledge.

Stern, Y. (2012). Cognitive reserve in aging and Alzheimer's disease. Lancet Neurol, 11(11):1006-12.

Thurstone, L.L. (1938). Primary mental abilities. University of Chicago Press: Chicago.

Tomlinson, C. A. (2017). How to differentiate instruction in academically diverse classrooms. ASCD.

Van Der Maas, H. L. J., Dolan, C. V., Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113(4), 842–861.

Van de Vijver, F. J., & Leung, K. (1997). Methods and data analysis for cross-cultural research. Sage Publications.

Warne, R. T., & Burningham, C. (2019). Spearman’s g found in 31 non-Western nations: Strong evidence that g is a universal phenomenon. Psychological Bulletin, 145(3), 237–272.

Waterhouse, L. (2006). Inadequate Evidence for Multiple Intelligences, Mozart Effect, and Emotional Intelligence Theories. Educational Psychologist, 41(4), 247–255.

Walter, F., Daseking, M., & Pauls, F. (2021). Sex Differences in Intelligence in Children Aged 2:6–7:7: Analysis of the Factor Structure and Measurement Invariance of the German Wechsler Primary and Preschool Scale of Intelligence–Fourth Edition. Journal of Psychoeducational Assessment, 39(4), 395–421.

Warne, R. T., & Burningham, C. (2019). Spearman’s g found in 31 non-Western nations: Strong evidence that g is a universal phenomenon. Psychological Bulletin, 145(3), 237–272.

Warne, R. T., Godwin, L. R., & Smith, K. V. (2013). Are There More Gifted People Than Would Be Expected in a Normal Distribution? An Investigation of the Overabundance Hypothesis. Journal of Advanced Academics, 24(4), 224–241.

Waschl, N. A., Nettelbeck, T., Jackson, S. A., & Burns, N. R. (2016). Dimensionality of the Raven’s Advanced Progressive Matrices: Sex differences and visuospatial ability. Personality and Individual Differences, 100, 157–166.

Waterhouse, L. (2006). Inadequate Evidence for Multiple Intelligences, Mozart Effect, and Emotional Intelligence Theories. Educational Psychologist, 41(4), 247–255.

Weiss, L. G., Saklofske, D. H., Prifitera, A., & Holdnack, J. A. (Eds.). (2010). WISC-V assessment and interpretation: Scientist-practitioner perspectives. Academic Press.

Weinberg, R. A. (1989). Intelligence and IQ: Landmark issues and great debates. American Psychologist, 44(2), 98–104.

Witmer, B. G., & Singer, M. J. (1998). Measuring presence in virtual environments: A presence questionnaire. Presence: Teleoperators and Virtual Environments, 7(3), 225–240.


  • There are currently no refbacks.

Copyright (c) 2024 Luis Anunciação, Anna C Portugal, Ivan Rabelo, Roberto Cruz, Louise Marques, Jesus Landeira-Fernandez

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Journal of Psychological Perspectives
Published by:
Lucky Arya Residence 2 No. 18
Jalan HOS. Cokroaminoto Kab. Pringsewu
Lampung - Indonesia, Postal code 35373

Creative Commons License
Journal of Psychological Perspectives is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.