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Bootstrapping adjustment (BA) method for item parameter bias reduction

Research Method · All research methods
Evidence · 1 claim (1 for) · 1 study (1 design), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description

BA is one of two item parameter adjustment methods proposed in the article, reducing biases in both item difficulty and item discrimination parameters using statistical bootstrapping. In four steps it repeatedly samples anchor students based on the unbiased ability estimates to form standard-normal-distributed samples of the same size, applies 2PL-IRT to each sample, and averages the resulting difficulty and discrimination estimates over K repetitions. The article states "The BA method relies on less constraint and could reduce the biases contained in both item discrimination and difficulty estimates", and that it "has the potential for applying on more complicated IRT models, such as 3PL-IRT"

Accounts

  • Bootstrapping adjustment (BA) method for item parameter bias reduction: BA is one of two item parameter adjustment methods proposed in the article, reducing biases in both item difficulty and item discrimination parameters using statistical bootstrapping. In four steps it repeatedly samples anchor students based on the unbiased ability estimates to form standard-normal-distributed samples of the same size, applies 2PL-IRT to each sample, and averages the resulting difficulty and discrimination estimates over K repetitions. The article states "The BA method relies on less constraint and could reduce the biases contained in both item discrimination and difficulty estimates", and that it "has the potential for applying on more complicated IRT models, such as 3PL-IRT" (Xue et al. (2020))

Claims

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Key Sources

  • Xue, K., Huggins-Manley, A. C., & Leite, W. (2020). Semi-supervised Learning Method for Adjusting Biased Item Difficulty Estimates Caused by Nonignorable Missingness under 2PL-IRT Model. Proceedings of The 13th International Conference on Educational Data Mining (EDM 2020), pp. 715-719. https://educationaldatamining.org/EDM2020/
Page metadata
Field Value
type research-method
id bootstrapping-adjustment-ba-method-for-item-parameter-bias-reduction
title Bootstrapping adjustment (BA) method for item parameter bias reduction
description BA is one of two item parameter adjustment methods proposed in the article, reducing biases in both item difficulty and item discrimination parameters using statistical bootstrapping.
status review
moved_from element/bootstrapping-adjustment-ba-method
generated by process:sweep-kinds on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — xue-2020

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