Comparability of IQ scores over time

Must, Olev; Nijenhuis, Jan te; Must, Anne; Vianen, A.E.M. van

doi:10.1016/j.intell.2008.05.002

Cited by 40 publications

(30 citation statements)

References 32 publications

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“…For example, is it due to differences in the intelligence instruments, differences in the analyses, differences between countries or is it due to actual differences in the magnitude and direction of this secular trend? Our analysis of the Estonian NIT data, in conjunction with other analysis of the same data [65,66], suggest that age may be a factor in the FE. Nonetheless, more FE scholarship utilizing multiple time periods and appropriate data analysis models is needed.…”

Section: Recommendationssupporting

confidence: 59%

“…Although they assumed only one growth pattern, they did find heterogeneity in the growth. Using different respondent subsets, Must, Must and Raudik [66] found aggregate score changes ranging from 0.04 (13âȂŞ14 year-olds) to 0.22 (12-13 year-olds) IQ points/year, while Must, te Nijenhuis, Must and van Vianen [65] found aggregate score changes ranging from 0.08 (14-15 year-olds) to 0.16 (13-14 year-olds) IQ points/year. Their reported score changes do not map directly onto the changes we found, but their results clearly support the idea of multiple patterns of change underlying the FE.…”

Section: Comparison With Previous Flynn Effect Research Using the Estmentioning

confidence: 99%

“…This data was collected in Estonia at three separate time points: 1934, 1998 and 2006. More information about the sample and the NIT can be found in previous studies using these data [7,9,65,66].…”

Section: National Intelligence Testsmentioning

confidence: 99%

See 2 more Smart Citations

An Investigation of Growth Mixture Models for Studying the Flynn Effect

Morgan

Beaujean

2014

J. Intell.

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The Flynn effect (FE) is the well-documented generational increase of mean IQ scores over time, but a methodological issue that has not received much attention in the FE literature is the heterogeneity in change patterns across time. Growth mixture models (GMMs) offer researchers a flexible latent variable framework for examining the potential heterogeneity of change patterns. The article presents: (1) a Monte Carlo investigation of the performance of the various measures of model fit for GMMs in data that resemble previous FE studies; and (2) an application of GMM to the National Intelligence Tests. The Monte Carlo study supported the use of the Bayesian information criterion (BIC) and consistent Akaike information criterion (CAIC) for model selection. The GMM application study resulted in the identification of two classes of participants that had unique change patterns across three time periods. Our studies show that GMMs, when applied carefully, are likely to identify homogeneous subpopulations in FE studies, which may aid in further understanding of the FE.

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Section: Recommendationssupporting

confidence: 59%

Section: Comparison With Previous Flynn Effect Research Using the Estmentioning

confidence: 99%

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An Investigation of Growth Mixture Models for Studying the Flynn Effect

Morgan

Beaujean

2014

J. Intell.

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“…We do not adopt this strategy because psychometricians have warned against the use of isolated subtests for the measurement of general cognitive ability (McDermott, Fantuzzo and Glutting 1990). Ensuring the comparability of cognitive tests is challenging, especially when studying test scores over time (see Must, te Nijenhuis, Must and Van Vianen 2009). Flynn (2012) highlights that performances on different cognitive ability subtests have improved at different rates.…”

Section: Datamentioning

confidence: 99%

An investigation of Social Class Inequalities in General Cognitive Ability in Two British Birth Cohorts

Connelly¹,

Gayle²

2018

Preprint

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The 'Flynn effect' describes the substantial and long-standing increase in average cognitive ability test scores, which has been observed in numerous psychological studies. Flynn makes an appeal for researchers to move beyond psychology's standard disciplinary boundaries and to consider sociological contexts, in order to develop a more comprehensive understanding of cognitive inequalities. In this article we respond to this appeal and investigate social class inequalities in general cognitive ability test scores over time. We analyse data from the National Child Development Study (1958) and the British Cohort Study (1970). These two British birth cohorts are suitable nationally representative large-scale data resources for studying inequalities in general cognitive ability. We observe a large parental social class effect, net of parental education and gender in both cohorts. The overall finding is that large social class divisions in cognitive ability can be observed when children are still at primary school, and similar patterns are observed in each cohort. Notably, pupils with fathers at the lower end of the class structure are at a distinct disadvantage. This is a disturbing finding and it is especially important because cognitive ability is known to influence individuals later in the lifecourse.

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“…There is also recent evidence of IQ test scores continuing to rise in countries in the former communist Eastern Europe (e.g. in Estonia, see Must, te Nijenhuis, Must, & van Vianen, 2009), in less-developed parts of the world, for example in Sudan (Khaleefa, Abdewahid, Abdulradi, & Lynn, 2008), Kenya (Daley, Whaley, Sigman, Espinosa, & Neumann, 2003), and in the Caribbean (Meisenberg, Lawless, Lambert, & Ross, 2006).…”

mentioning

confidence: 99%