Investigating item complexity as a source of cross-national DIF in TIMSS math and science

Huang, Qi; Bolt, Daniel M.; Lyu, Weicong

doi:10.1186/s40536-024-00200-3

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…Finally, the performance of our proposed error estimates could also be applied to mis-specified IRT models. For example, the 2PL model could be employed for linking if the item response data would be generated from the logistic positive exponential model [90,91] or the monotonic polynomial IRT model [92,93]. All of these limitations could be addressed in extensive future research.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model

Robitzsch

2024

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The two-parameter logistic (2PL) item response theory model is a statistical model for analyzing multivariate binary data. In this article, two groups are brought onto a common metric using the 2PL model using linking methods. The linking methods of mean–mean linking, mean–geometric–mean linking, and Haebara linking are investigated in nonrobust and robust specifications in the presence of differential item functioning (DIF). M-estimation theory is applied to derive linking errors for the studied linking methods. However, estimated linking errors are prone to sampling error in estimated item parameters, thus resulting in artificially increased the linking error estimates in finite samples. For this reason, a bias-corrected linking error estimate is proposed. The usefulness of the modified linking error estimate is demonstrated in a simulation study. It is shown that a simultaneous assessment of the standard error and linking error in a total error must be conducted to obtain valid statistical inference. In the computation of the total error, using the bias-corrected linking error estimate instead of the usually employed linking error provides more accurate coverage rates.

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Section: Discussionmentioning

confidence: 99%

Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model

Robitzsch

2024

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“…In this Simulation Study 2, we investigated the impact of misspecified IRT models. Item responses in this simulation study were simulated according to the logistic positive exponential (LPE) model (Samejima 2000;Bolt et al 2014;Bolfarine and Bazán 2010;Huang et al 2024). The IRF of the LPE model is given by…”

Section: Methodsmentioning

confidence: 99%

SIMEX-based and analytical bias corrections in Stocking-Lord linking

Robitzsch

2024

Preprint

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Stocking-Lord (SL) linking is a popular linking method for group comparisons based on dichotomous item responses. This article proposes a bias correction technique based on the simulation extrapolation (SIMEX) method for SL linking in the 2PL model in the presence of uniform differential item functioning (DIF). The SIMEX-based method is compared to analytical bias correction methods of SL linking. It turned out in a simulation study that SIMEX-based SL linking performed best, is easy to implement, and can be adapted to other linking methods straightforwardly.

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“…Such DIF and DSF effects have to be taken into account in psychometric analyses (e.g., Bolt & Stout, 1996;Camilli, 2006;Holland & Thayer, 1986; Q. Huang et al, 2024;X. Huang et al, 2016;Penfield, 2007;Penfield & Algina, 2003;Suh & Bolt, 2011;Zwick & Thayer, 1996;Zwick et al, 1993).…”

Section: Introductionmentioning

confidence: 99%

Partial credit trees meet the partial gamma coefficient for quantifying DIF and DSF in polytomous items

Henninger,

Radek,

Sengewald

et al. 2024

Preprint

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Partial credit trees (PCtree) from the model-based recursive partitioning framework combine the partial credit measurement model for polytomous items with decision trees from machine learning. This method allows researchers to investigate measurement invariance by detecting differential item and differential step functioning (DIF/DSF) in a data driven way. In this manuscript, we extend PCtrees by an effect size measure for DIF/DSF in polytomous items, the partial gamma coefficient from psychometrics. We evaluate this extension of PCtrees in a series of simulation studies. Our results show that the partial gamma coefficient supports researchers in evaluating whether splits in the tree are meaningful, identifying DIF and DSF items, and can stop the tree from growing in case of negligible effect sizes. Furthermore, we assess and implement a correction for item-wise testing that is particularly crucial in longer tests. Finally, we illustrate the extension of PCtrees using data from the LISS panel to showcase its enhanced interpretability.

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Investigating item complexity as a source of cross-national DIF in TIMSS math and science

Cited by 4 publications

References 25 publications

Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model

Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model

SIMEX-based and analytical bias corrections in Stocking-Lord linking

Partial credit trees meet the partial gamma coefficient for quantifying DIF and DSF in polytomous items

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