Table 4.

Item parameter estimates and model fit indices for the GRM (Items i1–i12)

Item	α	β₁	β₂	β₃	β₄	Infit	Outfit	S-χ²	df	RMSEA	p-value
i1	2.56	−1.08	0.09	1.04	2.47	0.903	0.878	37.80	36	0.013	0.388
i2	2.44	−1.19	0.14	1.21	2.51	0.902	0.888	28	34	0.000	0.756
i3	2.37	−1.36	0.09	1.18	2.73	0.897	0.901	48.60	34	0.038	0.050
i4	2.71	−1.15	0.08	1.01	2.34	0.908	0.943	39.90	34	0.025	0.223
i5	2.44	−1.21	0.09	1.25	2.53	0.887	0.888	45.50	34	0.034	0.090
i6	2.35	−1.04	0.19	1.18	2.55	0.886	0.880	40	37	0.017	0.337
i7	2.26	−1.27	0.08	1.26	2.64	0.919	0.936	42	35	0.026	0.193
i8	2.46	−1.16	0.09	1.19	2.74	0.887	0.881	25.20	33	0.000	0.832
i9	2.17	−1.13	0.17	1.29	2.66	0.910	0.909	48.70	37	0.033	0.095
i10	2.01	−1.13	0.11	1.27	2.40	0.902	0.888	49.20	41	0.026	0.177
i11	2.19	−1.25	0.09	1.26	2.79	0.922	0.921	30	35	0.000	0.706
i12	2.95	−1.14	0.10	1.11	2.62	0.884	0.866	33.20	32	0.011	0.409

α = item discrimination parameter; β₁–β₄ = category thresholds; Infit/Outfit = item fit mean squares; S-χ² = item-level chi-square fit statistic; RMSEA = root mean square error of approximation; p-value corresponds to the item-level fit test. RMSEA values of 0 indicate χ² ≤ df (excellent fit)