Estimating ability from items isomorphs: effects on the reliability of the test scores

En este artículo se aborda el problema de la imprecisión en los parámetros de los ítems y su efecto las puntuaciones de los sujetos en los tests adaptativos. En particular se considera la imprecisión introducida en el test por el proceso de incluir ítems isomorfos en el banco. La investigación se lleva a cabo mediante un estudio de Monte Carlo en el que la precisión se calcula bajo diferentes niveles de error en los parámetros de los ítems. Los resultados indican que el proceso de creación de isomorfos puede ser una alternativa viable, pero es necesario previamente obtener una estimación del error introducido por dicho procesoThis article focuses on the errors of the item parameter estimates and their effect on the reliability of the test scores. In particular we consider the errors introduced by the process of creating item isomorphs. The research is conducted by means of a Monte Carlo simulation. The simulation includes several conditions r egarding the size of the errors and the number of isomorphs in the item pool of an adaptive test. The results show that the errors due to the isomorphing process do not compromise the psychometric status of the test scores except in the condition with highest errorsEsta investigación ha sido financiada en parte por el proyecto de la DGICYT PB 97-004

Logistic response models with item interactions

Items that are clustered according to shared content may violate the principle of conditional independence commonly used in item response theory. This paper investigates the capabilities of a logistic item response model in relation to locally dependent item responses. The model includes main effect and interaction parameters that are computed as linear functions of the latent trait. The paper explains the interpretation of the parameters, the maximum likelihood estimation algorithm, the information matrix and some results concerning parameter identifiability. The problem of over-fitting the data is addressed in a simulation study, and two real data examples are described to illustrate the approach, one from the context of a sample survey and the other from ability testing using testlets

Bayesian dimensionality assessment for the multidimensional nominal response model

This article introduces Bayesian estimation and evaluation procedures for the multidimensional nominal response model. The utility of this model is to perform a nominal factor analysis of items that consist of a finite number of unordered response categories. The key aspect of the model, in comparison with traditional factorial model, is that there is a slope for each response category on the latent dimensions, instead of having slopes associated to the items. The extended parameterization of the multidimensional nominal response model requires large samples for estimation. When sample size is of a moderate or small size, some of these parameters may be weakly empirically identifiable and the estimation algorithm may run into difficulties. We propose a Bayesian MCMC inferential algorithm to estimate the parameters and the number of dimensions underlying the multidimensional nominal response model. Two Bayesian approaches to model evaluation were compared: discrepancy statistics (DIC, WAICC, and LOO) that provide an indication of the relative merit of different models, and the standardized generalized discrepancy measure that requires resampling data and is computationally more involved. A simulation study was conducted to compare these two approaches, and the results show that the standardized generalized discrepancy measure can be used to reliably estimate the dimensionality of the model whereas the discrepancy statistics are questionable. The paper also includes an example with real data in the context of learning styles, in which the model is used to conduct an exploratory factor analysis of nominal dataThis research was partially supported by grants PSI2012-31958 and PSI2015-66366-P from the Ministerio de Economía y Competitividad (Spain

Una solución a la estimación inicial en los test adaptativos informatizados

A new method for computing ability estimates when the response vector contains only errors or correct responses is proposed. It is based on the Stepsize method (Dodd, 1990). Instead of taking as the new ability the midpoint between the last computed ability and the corresponding extreme b- value, the new method proposes as the new estimate the mean of a truncated normal (0, 1) distribution. Last ability estimate and the correponding extreme b-value are the points in which the normal distribution truncates.El trabajo ha recibido financiación parcial de dos proyectos DGICYT (PS94-0040 y PS95-0046

El ICMA instala un nuevo detector de neutrones en el Institut Laue-Langevin

Página web divulgativa.El Instituto de Ciencia Materiales de Aragón (ICMA) ha desarrollado un detector de neutrones, y ya lo está instalando en el Institut Laue-Langevin (ILL) de Grenoble (Francia), centro de referencia mundial en técnicas neutrónicas. Además, el Instituto gestionará para toda España los instrumentos españoles del ILL.Peer Reviewe

Mean structure analysis from an IRT approach: an application in the context of organizational psychology

The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fi t. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchersAnálisis de estructura de medias mediante un modelo TRI: una aplicación en el contexto de la psicología de las organizaciones. La aplicación de modelos de análisis de estructura de medias y covarianzas en datos cuantitativos está extendiéndose. Sin embargo, el análisis de medias latentes a partir de datos cualitativos es menos habitual. Este artículo resume los procedimientos para llevar a cabo un análisis de estructura de medias latentes con ítems dicotómicos desde un enfoque de la teoría de respuesta al ítem. Se ilustra la implementación de dichos procedimientos en un ejemplo con datos empíricos referidos al contexto organizacional, donde se lleva a cabo un análisis multigrupo para comparar las medias latentes de tres grupos de empleados en dos factores que miden preferencias personales y el grado percibido en que la organización las refuerza. Los resultados indican que a mayor motivación personal, se necesita mayor refuerzo por parte de la organización, y que existen diferencias entre grupos, ocurriendo que los empleados que ocupan posiciones más altas tienen menor nivel de motivaciones personales y organizacionales. El artículo muestra cómo estimar las medias y correlaciones de los factores de ítems dicotómicos, y cómo evaluar la bondad de ajuste. Por último, se muestra la sintaxis M-Plus para facilitar la aplicación de este tipo de análisis a los investigadoresThis work was partially supported by grant CCG08-UAM/ESP-3951 of the Comunidad of Madrid (Spain) and grant PSI2009-08264 of the Spanish Ministry of Science and Innovatio