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An Evaluation of S pearman's H ypothesis by Manipulating g Saturation
Author(s) -
McDaniel Michael A.,
Kepes Sven
Publication year - 2014
Publication title -
international journal of selection and assessment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.812
H-Index - 61
eISSN - 1468-2389
pISSN - 0965-075X
DOI - 10.1111/ijsa.12081
Subject(s) - psychology , saturation (graph theory) , statistics , aptitude , cognition , test (biology) , social psychology , econometrics , developmental psychology , mathematics , ecology , biology , combinatorics , neuroscience
S pearman's Hypothesis holds that the magnitude of mean W hite– B lack differences on cognitive tests covaries with the extent to which a test is saturated with g . This paper evaluates S pearman's H ypothesis by manipulating the g saturation of cognitive composites. Using a sample of 16,384 people from the General Aptitude Test Battery database, we show that one can decrease mean racial differences in a g test by altering the g saturation of the measure. Consistent with S pearman's Hypothesis, the g saturation of a test is positively and strongly related to the magnitude of W hite– B lack mean racial differences in test scores. We demonstrate that the reduction in mean racial differences accomplished by reducing the g saturation in a measure is obtained at the cost of lower validity and increased prediction errors. We recommend that g tests varying in mean racial differences be examined to determine if the S pearman's Hypothesis is a viable explanation for the results.