Browsing by Author "Wiberg, Marie"

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    A Family of Discrete Kernels for Presmoothing Test Score Distributions
    (Springer, 2024) González Burgos, Jorge Andrés; Wiberg, Marie
    In the fields of educational measurement and testing, score distributions are often estimated by the sample relative frequency distribution. As many score distributions are discrete and may have irregularities, it has been common practice to use presmoothing techniques to correct for such irregularities of the score distributions. A common way to conduct presmoothing has been to use log-linear models. In this chapter, we introduce a novel class of discrete kernels that can effectively estimate the probability mass function of scores, providing a presmoothing solution. The chapter includes an empirical illustration demonstrating that the proposed discrete kernel estimates perform as well as or better than the existing methods like log-linear models in presmoothing score distributions. The practical implications of this finding are discussed, highlighting the potential benefits of using discrete kernels in educational measurement contexts. Additionally, the chapter identifies several areas for further research, indicating opportunities for advancing the field’s methodology and practices.
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    A Note on the Poisson's Binomial Distribution in Item Response Theory
    (2016) González Burgos, Jorge Andrés; Wiberg, Marie; von Davier, Alina A.
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    Applying test equating methods, using R
    (2017) González Burgos, Jorge Andrés; Wiberg, Marie
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    Generalized Kernel Equating with Applications in R
    (Taylor & Francis, 2024) Wiberg, Marie; González Burgos, Jorge Andrés; von Davier, Alina A.
    Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons.The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.
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    Possible Factors Which May Impact Kernel Equating of Mixed-Format Tests
    (Springer Cham, 2021) Wiberg, Marie; González Burgos, Jorge Andrés
    Mixed-format tests contain items with different formats such as dichotomously scored and polytomously scored items. The aim of this study was to examine the impact of item discrimination, sample size, and proportion of polytomously scored items on item response theory (IRT) kernel equating of mixed-format tests under the equivalent groups design. A simulation study was performed to examine the aim. The results from the simulation study showed that the percent relative errors were low and stable for all conditions, whereas differences in standard errors and equated values where found for the conditions with different sample sizes and item discriminations. Also, the standard errors were higher when the proportion of polytomously scored items in the test where higher.
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    Practical implementation of test equating using r
    (Springer, 2020) Wiberg, Marie; González Burgos, Jorge Andrés
    Test equating methods are widely used in order to make comparable different test forms administered at different occasions to different test takers. Although software for test equating is currently available, in this paper we focus the attention on four different R packages which can facilitate test equating for researchers and test developers. This paper list the different R packages which are available at the moment. Examples are provided for the equate, equateIRT, kequate, and the SNSequate packages. Additional features of these packages are discussed as well.
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    Statistical Assessment of Estimated Transformations in Observed-Score Equating
    (2016) Wiberg, Marie; González Burgos, Jorge Andrés