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A Bayesian item response model for examining item position effects in complex survey data. / Trendtel, Matthias; Robitzsch, Alexander.

In: Journal of Educational and Behavioral Statistics, Vol. 46, No. 1, 02.2021, p. 34-57.

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Trendtel, M & Robitzsch, A 2021, 'A Bayesian item response model for examining item position effects in complex survey data', Journal of Educational and Behavioral Statistics, vol. 46, no. 1, pp. 34-57. https://doi.org/10.3102/1076998620931016

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Author

Trendtel, Matthias ; Robitzsch, Alexander. / A Bayesian item response model for examining item position effects in complex survey data. In: Journal of Educational and Behavioral Statistics. 2021 ; Vol. 46, No. 1. pp. 34-57.

BibTeX

@article{ecb73f99cc8144bc9c9a8c83a5a174c2,
title = "A Bayesian item response model for examining item position effects in complex survey data",
abstract = "A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on the item side as well as on the person side. Moreover, a flexible loading structure on the two dimensions is allowed. A fully Bayesian estimation procedure is proposed, and its performance is investigated by a simulation study. Further, the model is applied to empirical data collected in the Programme for International Student Assessment 2000 in the reading domain. The additional value of the model{\textquoteright}s extended flexibility compared to more restrictive models is shown. The findings show that the linear hypothesis of change in performance during a test does not hold in general.",
keywords = "Bayesian IRT, MCMC estimation, complex survey data, multidimensional IRT, item position effects",
author = "Matthias Trendtel and Alexander Robitzsch",
year = "2021",
month = feb,
doi = "10.3102/1076998620931016",
language = "English",
volume = "46",
pages = "34--57",
journal = "Journal of Educational and Behavioral Statistics",
issn = "1076-9986",
publisher = "Sage",
number = "1",

}

RIS

TY - JOUR

T1 - A Bayesian item response model for examining item position effects in complex survey data

AU - Trendtel, Matthias

AU - Robitzsch, Alexander

PY - 2021/2

Y1 - 2021/2

N2 - A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on the item side as well as on the person side. Moreover, a flexible loading structure on the two dimensions is allowed. A fully Bayesian estimation procedure is proposed, and its performance is investigated by a simulation study. Further, the model is applied to empirical data collected in the Programme for International Student Assessment 2000 in the reading domain. The additional value of the model’s extended flexibility compared to more restrictive models is shown. The findings show that the linear hypothesis of change in performance during a test does not hold in general.

AB - A multidimensional Bayesian item response model is proposed for modeling item position effects. The first dimension corresponds to the ability that is to be measured; the second dimension represents a factor that allows for individual differences in item position effects called persistence. This model allows for nonlinear item position effects on the item side as well as on the person side. Moreover, a flexible loading structure on the two dimensions is allowed. A fully Bayesian estimation procedure is proposed, and its performance is investigated by a simulation study. Further, the model is applied to empirical data collected in the Programme for International Student Assessment 2000 in the reading domain. The additional value of the model’s extended flexibility compared to more restrictive models is shown. The findings show that the linear hypothesis of change in performance during a test does not hold in general.

KW - Bayesian IRT

KW - MCMC estimation

KW - complex survey data

KW - multidimensional IRT

KW - item position effects

U2 - 10.3102/1076998620931016

DO - 10.3102/1076998620931016

M3 - Journal article

VL - 46

SP - 34

EP - 57

JO - Journal of Educational and Behavioral Statistics

JF - Journal of Educational and Behavioral Statistics

SN - 1076-9986

IS - 1

ER -

ID: 1389758