An Empirical Study of the Stability of a Group Mean in Relation to the Distribution of Test Items Among Students

Johnson, M. Clemens; Lord, Frederic M.

doi:10.1177/001316445801800209

Cited by 10 publications

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“…Notes 1. Note that in large-scale assessment, the idea of sampling and associated variability extends beyond sampling examinees to item sampling from a theoretical population or universe of test items (Johnson & Lord, 1958;Shoemaker, 1973). The concept of item sampling-commonly referred to in modern literature as matrix sampling-underpins the methods used for assessment design and achievement estimation in international large-scale assessment (Mislevy, 1984;Mislevy et al, 1992;Rutkowski et al, 2014).…”

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confidence: 99%

Generalizing Beyond the Test: Permutation-Based Profile Analysis for Explaining DIF Using Item Features

Bolsinova¹,

Tijmstra

Rutkowski³

et al. 2023

Journal of Educational and Behavioral Statistics

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Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test whether conclusions about the item-feature effects generalize outside of the considered set of items. This article addresses both of these limitations, by generalizing profile analysis to work under the two-parameter logistic model and by proposing a permutation test that allows for generalizable conclusions about item-feature effects. The developed methods are evaluated in a simulation study and illustrated using Programme for International Student Assessment 2015 Science data.

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