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Aplicación del Modelo de Respuesta Graduada a una Escala de Voluntad de Trabajo

Keywords: graded response model, samejima′s model, will-to-work, item response theory.

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Abstract:

this study aims to present the findings obtained from the application of an item responsetheory model (irt) to the reactive of a will-to-work measuring test (ww). ww is defined as the individuals' tendency to generate efficient volatile processes that allow them to commit themselves to starting a task and to persisting in its execution by overcoming obstacles until they achieve its materialization with precision and without procrastination. ww is a personality trait that describes the predisposition of an individual to assume duties in a responsible, self-motivated and prompt manner even when such duties may be unappealing. the scale measuring the ww comprises 9 items in polychromous response format (four-point rating scale), with the response options graded. accordingly, one of the irt most widely used models was applied for the monetization of ordered polychromous responses: samejima's graded response model (grm). the grm is a generalization of the two parameter logistic model of birnbaum. in grm, a person's probability of responding in category j to a specific item i, pij(θ), is obtained by subtracting the probability of responding in or below category j-1 from the probability of responding in or below category j.through the item response category curves, the grm allows for the representation of an individual's likelihood to choose each of the item categories based on the level of the latent trait measured. the data from this psychometric test was obtained from a sample of 1,141 university students. the one-dimensional assumption required by the grm was corroborated through an exploratory analysis of the data factor structure. the local independence assumption was considered to be satisfied after proving the scale one-dimensionality. all analyses based on the irt were performed by operating the multilog software program. the grm parameters estimation was carried out through marginal maximum likelihood procedures. a discrimination parameter (a) and three location

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