Bartholomew, David J., Allerhand, Michael and Deary, Ian J. (2013) Measuring mental capacity: Thomson's bonds model and Spearman's g-model compared. Intelligence and National Security, 41 (4). pp. 222-233. ISSN 0268-4527
Full text not available from this repository.Abstract
A contemporary version of Thomson's Bonds model for intelligence was proposed in Bartholomew et al. (2009). It was shown there that, as far as existing data was concerned, it could compete on equal terms, biologically and statistically with Spearman's long-established g-model. In this paper we take the further, crucial, step of showing how to fit and interpret the Bonds model. We shall show that although the two models are statistically indistinguishable, they offer radically different interpretations of how the brain works. In particular, we show that:. i)The Bonds model suggests a way of measuring individual ability (or mental capacity) from test scores by introducing the notion of what we shall call the power or mental capacity of the brain. This is analogous to, but not equivalent to, Spearman's g.ii)The model can be generalised to allow for the possibility that the brain makes several 'passes' through the test items. This identifies different characteristics of the items rather than different dimensions of ability as with Spearman's model.iii)The Bonds model does not require each person to have the same number of bonds as Spearman appears to have mistakenly supposed.The methods are illustrated on two data sets and an R package including functions and data sets is provided to enable the reader to explore the model in more detail. The authors produced a contemporary model of Thomson's bonds model of intelligence. The bonds model competes with Spearman' s g model on statistical and biological terms. This paper shows how to fit and interpret the bonds model. Spearman's and Thomson's models offer different interpretations of how the brain works. An R package is provided to allow the reader to explore the bonds model in more detail.
| Item Type: | Article |
|---|---|
| Official URL: | http://www.journals.elsevier.com/intelligence/ |
| Additional Information: | © 2013 Elsevier Inc |
| Divisions: | Statistics |
| Subjects: | Q Science > Q Science (General) |
| Date Deposited: | 28 May 2013 12:36 |
| Last Modified: | 06 Nov 2024 21:54 |
| URI: | http://eprints.lse.ac.uk/id/eprint/50426 |
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