86 research outputs found

    Dimensionality assessment under nonparametric IRT models

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    Theoretical and practical foundations of mokken scale analysis in psychology

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    La Teoría de Respuesta al Ítem representa uno de los mayores avances en el campo del desarrollo de medidas válidas en psicología. Entre los principales modelos utilizados en esta perspectiva se encuentran los modelos logísticos. Estos modelos no son adecuados para todas las aplicaciones en psicología, ya que algunas bases de datos en psicología no satisfacen las suposiciones de estos modelos: unidimensionalidad; monotonicidad latente; e independencia local; y, para algunos modelos, funciones que no se interceptan. Teniendo en cuenta este marco, el objetivo de este estudio fue presentar los fundamentos teóricos y prácticos del Análisis de la Escala de Mokken (AEM). Presentamos algunas cuestiones históricas relacionadas con el desarrollo de AEM, además de las principales características y suposiciones de los dos modelos utilizados en esta perspectiva. Después de ejemplificar un AEM, se presentan las limitaciones y consideraciones finales, apoyando o procesando la tomada de decisión para investigadores que van a usar el AEM.A Teoria de Resposta ao Item representa um dos principais avanços para a construção de medidas válidas e confiáveis em psicologia. Entre os principais modelos utilizados nessa perspectiva estão o modelo de Rasch e os modelos logísticos. Esses modelos paramétricos, no entanto, não podem ser utilizados em todas as aplicações em psicologia, uma vez que um número substancial dos bancos de dados em psicologia não satisfaz os pressupostos desses modelos: unidimensionalidade; monotonicidade latente; independência local; e, para alguns modelos, não-interseção de funções. Dessa forma, o objetivo deste estudo foi apresentar os fundamentos teóricos e práticos da Análise de Escala de Mokken (AEM). São apresentadas questões históricas envolvendo o desenvolvimento da AEM, além das principais características e pressupostos dos dois modelos usados nessa perspectiva. Após exemplificação de uma AEM, limitações e considerações finais são apresentadas, apoiando o processo de tomada decisão para pesquisadores que venham a usar a AEM.Item Response Theory represents one of the major advances in the field of developing valid and reliable measures in psychology. Among the main models used in this perspective are the Rasch model and the logistic models. These parametric models, however, are not suitable for all applications in psychology, since a substantial number of databases in psychology do not satisfy the assumptions of these models: unidimensionality; latent monotonicity; local independence; and, for some models, non-intersecting functions. Given this framework, the objective of this study was to present the theoretical and practical foundations of Mokken Scale Analysis (MSA). We present some historical issues involving the development of MSA, in addition to the main characteristics and assumptions of the two models used in this perspective. After exemplifying a MSA application, limitations and final considerations are presented, supporting the decision-making process for researchers who come to use MSA

    Analysis of an Intelligence Dataset

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    In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type

    The Use of Nonparametric Item Response Theory to Explore Data Quality

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    The aim of this chapter is to provide insight into a number of commonly used nonparametric item response theory (NIRT) methods and to show how these methods can be used to describe and explore the psychometric quality of questionnaires used in patient-reported outcome measurement and, more in general, typical performance measurement (personality, mood, health-related constructs). NIRT is an extremely valuable tool for preliminary data analysis and for evaluating whether item response data are acceptable for parametric IRT modeling. This is in particular useful in the field of typical performance measurement where the construct being measured is often very different than in maximum performance measurement (education, intelligence; see Chapter 1 of this handbook). Our basic premise is that there are no “best tools” or “best models” and that the usefulness of psychometric modeling depends on the specific aims of the instrument (questionnaire, test) that is being used. Most important is, however, that it should be clear for a researcher how sensitive a specific method (for example, DETECT, or Mokken scaling) is to the assumptions that are being investigated. The NIRT literature is not always clear about this, and in this chapter we try to clarify some of these ambiguities
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