Efficacy of Effect Size Measures in Logistic Regression

Abstract

Statistical techniques based on logistic regression (LR) are adequate for the detection of differential item functioning (DIF) in dichotomous items. Nevertheless, they return more false positives (FPs) than do other DIF detection techniques. This paper compares the efficacy of DIF detection using the LR significance test and the estimation of the effect size that these procedures provide using R2 of Nagelkerke. The variables manipulated were different conditions of sample size, focal and reference group sample size ratio, amount of DIF, test length and percentage of test items with DIF. In addition, examinee responses were generated to simulate both uniform and nonuniform DIF (symmetric and asymmetric). In all cases, dichotomous response tests were used. The results show that the use of R2 as a strategy for detecting DIF obtained lower correct detection percentages than those obtained from significance tests. Moreover, the LR significance test showed adequate control of FP rates, close to the nominal 5%, although the rate was slightly higher than the nominal 5% when the sample size was smaller. However, when the effect size measure was used to detect DIF, the FP rates were lower and <1% for a wide number of conditions. In addition, a statistically significant main effect of the sample size variable was obtained. Thus, the FP percentages were higher when the sample size was small (100/100). The results obtained indicate that the use of R2 as a measure of effect size together with the statistical significance test reduces the rate of FP.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 34 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.