Abstract

GOMES, Carlos F. A.  and  BURATTO, Luciano G.. Multinomial modeling applied to psychological research. Psicol. pesq. [online]. 2020, vol.14, n.3, pp. 44-65. ISSN 1982-1247.  http://dx.doi.org/10.34019/1982-1247.2020.v14.29542.

Theories about psychological phenomena often refer to unobservable processes (latent processes). Traditionally, however, the psychological investigation of these phenomena is done indirectly to the latent processes themselves. The objective of this article is to introduce fundamental concepts about multinomial modeling. Here we show that latent processes models are derived from purely descriptive models by reducing the parameter space according to one or more psychological theories. The result is multinomial models that deliver simple measures of psychological processes (probabilities) and that can be tested quantitatively with real data. The use of multinomial modeling allows direct analysis of the effects of independent variables on the latent processes that control performance on one or more experimental tasks, thus making it easier to test theoretical predictions and explanations about psychological phenomena.

Keywords : Mathematical modeling; Latent processes; Multinomial distribution; Stochastic processes; Mental states.

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