Item | N = 344 | Measure (logits) | SEM | Measure (0–100 scale) | SEM | Infit MNSQ | Outfit MnSQ |
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1 | 342 | -1.95 | 0.13 | 33.3 | 0.9 | 0.97 | 0.93 |
3 | 339 | -1.38 | 0.12 | 37.3 | 0.9 | 0.98 | 0.94 |
2 | 342 | -1.32 | 0.12 | 37.7 | 0.9 | 0.94 | 0.91 |
7 | 334 | -0.76 | 0.12 | 41.7 | 0.9 | 0.82 | 0.81 |
8 | 319 | -0.35 | 0.12 | 44.7 | 0.9 | 0.92 | 0.88 |
6 | 328 | -0.21 | 0.12 | 45.7 | 0.9 | 1.34 | 1.30 |
4 | 277 | 0.30 | 0.13 | 49.3 | 0.9 | 1.23 | 1.20 |
11 | 313 | 0.53 | 0.12 | 50.9 | 0.8 | 0.86 | 0.87 |
10 | 324 | 0.85 | 0.11 | 53.2 | 0.8 | 0.99 | 1.01 |
9 | 287 | 0.86 | 0.12 | 53.3 | 0.8 | 0.91 | 0.94 |
5 | 314 | 0.86 | 0.11 | 53.3 | 0.8 | 1.28 | 1.29 |
12 | 289 | 1.11 | 0.11 | 55.1 | 0.8 | 0.67 | 0.69 |
13 | 305 | 1.45 | 0.11 | 57.5 | 0.8 | 1.05 | 1.16 |
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Measure (logits): The estimate for the item difficulty in logits.
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Measure (0–100 scale): The rescaled estimate for the item difficulty.
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SEM: The standard error of measurement in estimation of the item difficulty. SEM is the precision of the item difficulty estimation and is shown in logits and 0–100 units.
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Infit MNSQ: Infit mean square error is one of two quality control fit statistics assessing item dimensionality (the degree to which the item falls on the same single, real number line as the rest of the items). Infit is an information-weighted residual of observed responses from model expected responses and is most sensitive to item fit when the item is located near the person's scale location.
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Outfit MNSQ: Outfit mean square error fit statistic is most sensitive to item dimensionality when the item scale location is distant from the person's scale location [4].