Raters differed significantly in severity/leniency in the MFRM analysis¶

Claim · All claims
Evidence · 1 study · associational r2 · q3
Currency · newest study 2018 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2021: tool and model accuracy changes quickly

Subclaims¶

q3 i? The chi-square value for the rater facet was significant, indicating the three raters differed in severity/leniency. → Ilhan 2018

Evidence¶

Ilhan 2018¶

Ilhan, M., & Guler, N. (2018). A Comparison of Difficulty Indices Calculated for Open-Ended Items According to Classical Test Theory and Many Facet Rasch Model. Eurasian Journal of Educational Research, 75. doi:10.14689/ejer.2018.75.6

q3 · i? · associational · r2

MFRM analysis (FACETS) of the crossed-design rating data; Table 2 reports a rater-facet chi-square of 3063.3 (p<.001), separation ratio 39.11, reliability 1.00. Despite rater differences, item and person facet reliabilities were above .80.

"According to Table 2, the chi-square value for the rater facet is significant and the reliability coefficient and the separation ratio are high. This result indicates that the raters differ ed in severity/leniency."

Studies bearing on this claim¶

Do markers scoring the same responses agree, and do written criteria bring their judgements closer? This table gathers the studies behind this claim and the 7 narrower claims that bear on it: 9 distinct studies (3 associational, 3 causal, 3 design), q2–q3, 0 of 9 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

Related Claims¶

• Performance assessments can be reliably scored when designed appropriately and used with other measures — the general claim this finding bears on, with the studies behind it

• Criterion-referenced tests require empirically-based construct validation studies — the general claim this finding bears on, with the studies behind it

• CTT and MFRM yield similar item difficulty results for open-ended questions regardless of crossed or nested design — related
• The chi-square significance test for NC-DIF is overly sensitive at large sample sizes, requiring an empirical cutoff value — related
• Scorer severity and standard difficulty were statistically adjusted using Many-Facet Rasch analysis before assignment and work measures were compared — related
• Few models exist for estimating growth in the presence of multiple raters despite growing multi-rater longitudinal data — related
• Rubrics with parallel sentence structure, unambiguous wording and well-specified dimensions have lower grading variance, and revising rubrics decreased median grading error from 12.4% to 9.9% — related
• Rater selection via two-facet Rasch infit filtering substantially increases inter-rater reliability (Krippendorff's alpha) on ICNALE GRA — related