Related Experiment Video
Updated: Jul 2, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
A Simple Approach for Differential Test Functioning Based on Sum Scores
Yutaro Sakamoto1, Ryuichi Kumagai2
1Recruit Management Solutions Co., Ltd., Tokyo, Japan.
Abstract:
Differential test functioning (DTF) evaluates whether a test exhibits group differences beyond those attributable to latent trait differences. Its magnitude is often most interpretable on the raw-score scale. However, most existing DTF effect size measures rely on item response theory (IRT) modeling. Building on the renewed practical value of sum scores, this study proposes a simple observed-score-based approach to estimate the DTF magnitude directly in raw-score points. The proposed Index S stratifies examinees by an anchor-based sum score composed of items not flagged for differential item functioning (DIF), summarizes the within-stratum mean differences in total test scores, and aggregates these conditional differences using weights based on the observed distribution of the matching variable. To stabilize the estimation when score strata are sparse, adjacent strata are merged to satisfy a minimum per-group sample size requirement, and Index S_std provides a standardized version. We evaluated the indices using two-parameter logistic (2PL) simulation studies by varying the sample size, test length, DIF type, DIF proportion, DIF direction, and focal group latent trait distribution. The utility was assessed in terms of estimation accuracy, including Bias and root mean square error (RMSE), and correlation with established IRT-based DTF indices. An empirical application to TIMSS 2023 Grade 8 mathematics (Japan vs. the United States) illustrates how the proposed indices provide an accessible raw-score interpretation of the DTF magnitude for both psychometric and non-psychometric stakeholders.
Related Concept Videos
Bonferroni Test
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
Comparing Experimental Results: Student's t-Test
Friedman Two-way Analysis of Variance by Ranks
Significance Testing: Overview
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Introduction to the Sign Test

