Lord's chi-square identified more DIF items than Raju's unsigned area in the without-purification condition¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2021 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2024: tool and model accuracy changes quickly

Subclaims¶

q2 i? In pairwise booklet comparisons of the TEOG Turkish subtest, Lord's chi-square flagged a higher number of items with DIF than Raju's unsigned area when no item purification was applied. → Soysal 2021

Evidence¶

Soysal 2021¶

Soysal, S., & Yilmaz Kogar, E. (2021). An Investigation of Item Position Effects by Means of IRT-Based Differential Item Functioning Methods. International Journal of Assessment Tools in Education, 8(2), 239-256. https://doi.org/10.21449/ijate.779963

q2 · i? · associational · r2

Secondary analysis of real TEOG 2016 Turkish subtest response data from 9737 8th-grade students across four booklets, comparing DIF detection methods under the 3PL model. The article reports that "Lord's χ2 identified more items with DIF than Raju's unsigned area did in the without item purification condition."

"First, Lord's χ2 identified more items with DIF than Raju's unsigned area did in the without item purification condition."

Soysal 2021 (2)¶

Soysal, S., & Yilmaz Kogar, E. (2021). An Investigation of Item Position Effects by Means of IRT-Based Differential Item Functioning Methods. International Journal of Assessment Tools in Education, 8(2), 239-256. https://doi.org/10.21449/ijate.779963

q2 · i? · associational · r2

Same observational DIF analysis, with-purification condition: "fewer items with DIF were observed in the Raju's UA method than in the Lord's χ2 method", though the two methods' results were less consistent than without purification.

"In the condition of with item purification, as in the condition of without item purification, fewer items with DIF were observed in the Raju's UA method than in the Lord's χ2 method."

Discussion¶

Related Claims¶

• Item purification made both DIF methods more sensitive, flagging more items — related
• Item discrimination moderates detection differently by index: NCDIF benefits from high a-parameters only at large DIF magnitude — related
• The chi-square significance test for NC-DIF is overly sensitive at large sample sizes, requiring an empirical cutoff value — related
• Items flagged as DIF in booklet comparisons displayed non-uniform DIF in their item characteristic curves — related