Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-12-02T22:48:37.409Z Has data issue: false hasContentIssue false
  • English
  • Français

SPEARMAN’S HYPOTHESIS TESTED COMPARING SAUDI ARABIAN CHILDREN AND ADOLESCENTS WITH VARIOUS OTHER GROUPS OF CHILDREN AND ADOLESCENTS ON THE ITEMS OF THE STANDARD PROGRESSIVE MATRICES

Published online by Cambridge University Press:  07 November 2016

Jan Te NijenhuiS ,
Adel A. Batterjee ,
Michael Van Den Hoek ,
Jüri Allik  and
Vladimir Sukhanovskiy
Jan Te NijenhuiS*
Affiliation:
Work and Organizational Psychology, University of Amsterdam, the Netherlands
Adel A. Batterjee
Affiliation:
Waad Academy, Jeddah, Saudi Arabia
Michael Van Den Hoek
Affiliation:
Work and Organizational Psychology, University of Amsterdam, the Netherlands
Jüri Allik
Affiliation:
University of Tartu, Estonia
Vladimir Sukhanovskiy
Affiliation:
Parus Corporate, Moscow, Russia
*
1Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

Spearman’s hypothesis tested at the level of items states that differences between ethnic groups on the items of an IQ test are a function of the g loadings of these items, such that there are small differences between ethnic groups on items with low g loadings and large differences between ethnic groups on items with high g loadings; this has been confirmed in a limited number of studies. In this paper, Spearman’s hypothesis was tested, comparing a group of Saudi children and adolescents (N=3209) with other groups of children and adolescents from Denmark, Cyprus, Croatia, Bosnia, South Africa, Estonia, Ukraine, Ireland, Russia and Chile (total N=9333). The analyses were carried out on twelve comparisons between the Saudi Arabian children and the other children. Spearman’s hypothesis was confirmed less strongly than in other large-scale studies with a mean weighted r value of 0.44. The relevance of these findings for the discussion on the causes of group differences is discussed.

Type
Research Article
Information
Journal of Biosocial Science , Volume 49 , Issue 5 , September 2017 , pp. 634 - 647
Copyright
Copyright © Cambridge University Press, 2016 

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

Batterjee, A. A. (2011) Intelligence and education: the Saudi case. Mankind Quarterly 52, 133–190.Google Scholar
Dalliard. (2013) Spearman’s hypothesis and racial differences on the DAS-II. Humanvarieties.com. URL: http://humanvarieties.org/2013/12/08/spearmans-hypothesis-and-racial-differences-on-the-das-ii/ (accessed 24th March 2016).Google Scholar
Díaz, A., Sellami, K., Infanzón, E., Lanzón, T. & Lynn, R. (2012) A comparative study of general intelligence in Spanish and Moroccan samples. Spanish Journal of Psychology 15, 526–532.Google Scholar
Djapo, N. (2006) Internal and external validation of dynamic testing of intelligence. Doctoral dissertation, University of Sarajevo, Sarajevo, Bosnia-Herzegovina.Google Scholar
Djapo, N. & Lynn, R. (2010) Gender differences in means and variability on the Progressive Matrices in Bosnia-Herzegovina. Mankind Quarterly 50, 221–224.Google Scholar
Dolan, C. V., Roorda, W. & Wicherts, J. M. (2004) Two failures of Spearman’s hypothesis: the GATB in Holland and the JAT in South Africa. Intelligence 32, 155–173.Google Scholar
Flynn, J. R. (1984) The mean IQ of the Americans: massive gains 1932 to 1978. Psychological Bulletin 95, 29–51.Google Scholar
Flynn, J. R. (1987) Massive IQ gains in 14 nations: what IQ tests really measure. Psychological Bulletin 101, 171–191.Google Scholar
Flynn, J. R., te Nijenhuis, J. & Metzen, D. (2014) The g beyond Spearman’s g: Flynn’s paradoxes resolved using four exploratory meta-analyses. Intelligence 42, 1–10.Google Scholar
Gould, S. J. (1987) The Mismeasure of Man. Norton, New York.Google Scholar
Hartmann, P., Kruuse, N. H. S. & Nyborg, H. (2007) Testing the cross-racial generality of Spearman’s hypothesis in two samples. Intelligence 35, 47–57.Google Scholar
Hunter, J. E. (1986) Cognitive ability, cognitive aptitudes, job knowledge, and job performance. Journal of Vocational Behavior 29, 340–362.Google Scholar
Ivanovich, R., Forno, H., Durán, M. C., Game, J. H., Castro, J. & Ivanovich, C. (2000) Estudio de la capacidad intelectual (Test de matrices progresivas de Raven) en escolares chilenos de 5 a 18 años. I. Antecedentes generales, normas y recomendaciones [Study of the intellectual capacities (Raven Progressive Matrices Test) with Chilean school children aged 5 to 18 years old. I. General background information, norms, and recommendations]. Revista de Psicología General y Aplicada: Revista de la Federación Española de Asociaciones de Psicología 53, 5–30.Google Scholar
Jamieson, J. W. (2003) Some further thoughts on the subject of IQ population genetics. Mankind Quarterly 44, 211–232.Google Scholar
Jensen, A. R. (1980) Bias in Mental Testing. Free Press, New York.Google Scholar
Jensen, A. R. (1998) The g Factor: The Science of Mental Ability. Praeger, Westport, CT.Google Scholar
Lynn, R., Allik, J. & Irwing, P. (2004) Sex differences on three factors identified in Raven’s Standard Progressive Matrices. Intelligence 32, 411–424.Google Scholar
Lynn, R. & Owen, K. (1994) Spearman’s hypothesis and test score differences between Whites, Indians, and Blacks in South Africa. Journal of General Psychology 121, 27–36.Google Scholar
Lynn, R. & Vanhanen, T. (2002) IQ and the Wealth of Nations. Praeger, London.Google Scholar
Lynn, R. & Vanhanen, T. (2006) IQ and Global Inequality. Washington Summit, Atlanta, GA.Google Scholar
McHenry, J., Hough, L.M., Toquam, J. L., Hanson, M. A. & Ashworth, S. (1990) Project A validity results. The relationship between predictor and criterion domains. Personnel Psychology 43, 335–354.Google Scholar
Meisenberg, G. (2003) IQ population genetics: it’s not as simple as you think. Mankind Quarterly 44, 185–210.Google Scholar
Meisenberg, G. & Woodley, M. A. (2013) Are cognitive differences between countries diminishing? Evidence from TIMSS and PISA. Intelligence 41, 808–816.Google Scholar
Moran, A. P. (1986) The reliability and validity of Raven’s Standard Progressive Matrices for Irish apprentices. Applied Psychology 35, 533–538.Google Scholar
Nagoshi, C. T., Johnson, R. C., DeFries, J. C., Wilson, J. R. & Vandenberg, S. G. (1984) Group differences and first principal-component loadings in the Hawaii family study of cognition: a test of the generality of ‘Spearman’s hypothesis’. Personality and Individual Differences 5, 751–753.Google Scholar
Nisbett, R. E. (2009) Intelligence and How to Get It. Norton, New York.Google Scholar
Ogbu, J. U. (1994) Culture and intelligence. In Sternberg, R. J. (ed.) Encyclopedia of Human Intelligence. Macmillan, New York.Google Scholar
Owen, K. (1992) The suitability of Raven’s Standard Progressive Matrices for various groups in South Africa. Personality and Individual Differences 13, 149–159.Google Scholar
Prozorovskaya, I., Grigoriev, A. & Lynn, R. (2010) Gender differences in means and variability on the Standard Progressive Matrices for 15-year-olds in Ukraine. Mankind Quarterly 50, 297–310.Google Scholar
Piffer, D. (2015) A review of intelligence GWAS hits: their relationship to country IQ and the issue of spatial autocorrelation. Intelligence 53, 43–50.Google Scholar
Pullmann, H., Allik, J. & Lynn, R. (2004) The growth of IQ among Estonian schoolchildren from ages 7 to 19. Journal of Biosocial Science 36, 735–740.Google Scholar
Raven, J. C. (1958) Standard Progressive Matrices. Lewis, London.Google Scholar
Raven, J. (1960) Guide to the Standard Progressive Matrices sets A, B, C, D, and E. Lewis & Co., London.Google Scholar
Raven, J. C., Raven, J. E. & Court, J. H. (1998) Progressive Matrices. Oxford Psychologists Press, Oxford.Google Scholar
Ree, M. J. & Earles, A. A. (1991) Predicting training success: not much more than g . Personnel Psychology 44, 321–332.Google Scholar
Ree, M. J., Earles, J. A. & Teachout, M. S. (1994) Predicting job performance: not much more than g . Journal of Applied Psychology 79, 518–524.Google Scholar
Rindermann, H. (2008) Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence 36, 127–142.Google Scholar
Rindermann, H., Becker, D. & Coyle, T. R. (2016) Survey of expert opinion on intelligence: causes of international differences in cognitive ability tests. Frontiers in Psychology 7, 399.Google Scholar
Rindermann, H. & Thompson, J. (2013) Ability rise in NAEP and narrowing ethnic gaps? Intelligence 41, 821–831.Google Scholar
Rindermann, H. & Thompson, J. (2016) The cognitive competences of immigrant and native students across the world: an analysis of gaps, possible causes and impact. Journal of Biosocial Science 48, 66–93.Google Scholar
Rutter, M. (1985) Family and school influence on cognitive development. Journal of Child Psychology and Psychiatry 26, 683–704.Google Scholar
Rushton, J. P. (2002) Jensen effects and African/Coloured/Indian/White differences on Raven’s Standard Progressive Matrices in South Africa. Personality and Individual Differences 33, 1279–1284.Google Scholar
Rushton, J. P., Čvorović, J. & Bons, T. A. (2007) General mental ability in South Asians: data from three Roma (Gypsy) communities in Serbia. Intelligence 35, 1–12.Google Scholar
Rushton, J. P. & Jensen, A. R. (2003) African–White IQ differences from Zimbabwe on the Wechsler Intelligence Scale for Children-Revised are mainly on the g factor. Personality and Individual Differences 34, 177–183.Google Scholar
Rushton, J. P. & Jensen, A. R. (2005) Thirty years of research on race differences in cognitive ability. Psychology, Public Policy, and Law 11, 235–294.Google Scholar
Rushton, J. P. & Jensen, A. R. (2010) Race and IQ: a theory-based review of the research in Richard Nisbett’s Intelligence and How to Get It. Open Psychology Journal 3, 9–35.Google Scholar
Rushton, J. P. & Skuy, M. (2000) Performance on Raven’s Matrices by African and White university students in South Africa. Intelligence 28, 251–265.Google Scholar
Rushton, J. P., Skuy, M. & Fridjhon, P. (2002) Jensen effects among African, Indian, and White engineering students in South Africa on Raven’s Standard Progressive Matrices. Intelligence 30, 409–423.Google Scholar
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.Google Scholar
Schmidt, F. L. & Hunter, J. E. (1998) The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings. Psychological Bulletin 124, 262–274.Google Scholar
Spearman, C. (1927) The Abilities of Man: Their Nature and Measurement. Macmillan, New York.Google Scholar
ten Broeke, A. (2010) Onfatsoenlijke wetenschap is ook wetenschap [Indecent science is also science]. URL: http://www.kennislink.nl/publicaties/onfatsoenlijke-wetenschap-is-ook-wetenschap at 1-4-2010 (accessed 24th March 2016).Google Scholar
te Nijenhuis, J., Al-Shahomee, A. A., van den Hoek, M., Allik, J., Grigoriev, A. & Dragt, J. (2015a) Spearman’s hypothesis tested comparing Libyan secondary school children with various other groups of secondary school children on the items of the Standard Progressive Matrices. Intelligence 50, 118–124.Google Scholar
te Nijenhuis, J., Al-Shahomee, A. A., van den Hoek, M., Grigoriev, A. & Repko, J. (2015b) Spearman’s hypothesis tested comparing Libyan adults with various other groups of adults on the items of the Standard Progressive Matrices. Intelligence 50, 114–117.Google Scholar
te Nijenhuis, J., Bakhiet, S. F., van den Hoek, M., Repko, J., Allik, J., Žebec, M. S. et al. (2016a) Spearman’s hypothesis tested comparing Sudanese children and adolescents with various other groups of children and adolescents on the items of the Standard Progressive Matrices. Intelligence 56, 46–57.Google Scholar
te Nijenhuis, J., David, H., Metzen, D. & Armstrong, E. L. (2014a) Spearman’s hypothesis tested on European Jews vs non-Jewish Whites and vs Oriental Jews: two meta-analyses. Intelligence 44, 15–18.Google Scholar
te Nijenhuis, J., de Jong, M. J., Evers, A. & van der Flier, H. (2004a) Are cognitive differences between immigrant and majority groups diminishing? European Journal of Personality 18, 405–434.Google Scholar
te Nijenhuis, J., Evers, A. & Mur, J. P. (2000) Validity of the differential aptitude test for the assessment of immigrant children. Educational Psychology 20, 99–115.Google Scholar
te Nijenhuis, J., Grigoriev, A. & van den Hoek, M. (2016b) Spearman’s hypothesis tested in Kazakhstan on the items of the Standard Progressive Matrices Plus. Personality and Individual Differences 92, 191–193.Google Scholar
te Nijenhuis, J., Jongeneel-Grimen, B. & Kierkegaard, E. O. W. (2014b) Are Headstart gains on the g factor? A meta-analysis. Intelligence 46, 209–215.Google Scholar
te Nijenhuis, J., Jongeneel-Grimen, B. & Armstrong, E. (2015c) Are adoption gains on the g factor? A meta-analysis. Personality and Individual Differences 73, 56–60.Google Scholar
te Nijenhuis, J., Tolboom, E., Resing, W. & Bleichrodt, N. (2004b) Does cultural background influence the intellectual performance of children from immigrant groups? The RAKIT Intelligence Test for immigrant children. European Journal of Psychological Assessment 20, 10–26.Google Scholar
te Nijenhuis, J., van den Hoek, M. & Armstrong, E. L. (2015d) Spearman’s hypothesis and Amerindians: a meta-analysis. Intelligence 50, 87–92.Google Scholar
te Nijenhuis, J. & van der Flier, H. (1997) Comparability of GATB scores for immigrants and majority group members: some Dutch findings. Journal of Applied Psychology 82, 675–687.Google Scholar
te Nijenhuis, J. & van der Flier, H. (2005) Immigrant-majority group differences on work-related measures: the case for cognitive complexity. Personality and Individual Differences 38, 1213–1221.Google Scholar
te Nijenhuis, J. & van der Flier, H. (2013) Is the Flynn effect on g? A meta-analysis. Intelligence 41, 802–807.Google Scholar
te Nijenhuis, J., Willigers, D., Dragt, J. & van der Flier, H. (2016c) The effects of language bias and cultural bias estimated using the method of correlated vectors on a large database of IQ comparisons between native Dutch and ethnic minority immigrants from non-Western countries. Intelligence 54, 117–135.Google Scholar
van Rooijen, H. (2009) Nationaal IQ: Door zelfbedrog ingegeven domheid [National IQ: Stupidity inspired by self-deception]. Spiegeloog 37, 26–28.Google Scholar
Vejleskov, H. (1968) An analysis of Raven matrix responses in fifth grade children. Scandinavian Journal of Psychology 9, 177–186.Google Scholar
Woodley, M. A. (2012) The social and scientific temporal correlates of genotypic intelligence and the Flynn effect. Intelligence 40, 189–204.Google Scholar
Woodley, M. A., Rindermann, H., Bell, E., Stratford, J. & Piffer, D. (2014) The relationship between Microcephalin, ASPM and intelligence: a reconsideration. Intelligence 44, 51–63.Google Scholar
Woodley, M. A., te Nijenhuis, J., Must, O. & Must, A. (2014) Controlling for increased guessing enhances the independence of the Flynn effect from g: the return of the Brand effect. Intelligence 42, 27–34.Google Scholar
Žebec, M. S., Demetriou, A. & Kotrla-Topić, M. (2015) Changing expressions of general intelligence in development: a 2-wave longitudinal study from 7 to 18 years of age. Intelligence 49, 94–109.Google Scholar