From: Item fit statistics for Rasch analysis: can we trust them?
Outfit | Infit | ||||||
---|---|---|---|---|---|---|---|
n | k | uncond | cond | \(1\pm 6/\sqrt {n}\) | uncond | cond | \(1\pm 2/\sqrt {n}\) |
150 | 10 | 0.60–1.33 | 0.67–1.55 | 0.51–1.49 | 0.78–1.10 | 0.84–1.17 | 0.84–1.16 |
15 | 0.65–1.33 | 0.70–1.46 | 0.81–1.12 | 0.85–1.16 | |||
20 | 0.69–1.34 | 0.72–1.43 | 0.83–1.12 | 0.86–1.15 | |||
200 | 10 | 0.64–1.27 | 0.70–1.46 | 0.56–1.42 | 0.80–1.07 | 0.86–1.15 | 0.86–1.14 |
15 | 0.69–1.27 | 0.73–1.39 | 0.83–1.09 | 0.87–1.14 | |||
20 | 0.71–1.28 | 0.75–1.36 | 0.85–1.10 | 0.88–1.13 | |||
250 | 10 | 0.65–1.21 | 0.73–1.40 | 0.62–1.38 | 0.81–1.06 | 0.88–1.13 | 0.87–1.13 |
15 | 0.71–1.24 | 0.75–1.34 | 0.84–1.08 | 0.88–1.12 | |||
20 | 0.74–1.24 | 0.77–1.32 | 0.86–1.09 | 0.89–1.12 | |||
500 | 10 | 0.71–1.11 | 0.80–1.26 | 0.73–1.27 | 0.84–1.03 | 0.91–1.09 | 0.91–1.09 |
15 | 0.77–1.15 | 0.82–1.25 | 0.87–1.05 | 0.92–1.09 | |||
20 | 0.79–1.16 | 0.83–1.22 | 0.89–1.05 | 0.92–1.08 | |||
1000 | 10 | 0.76–1.05 | 0.85–1.18 | 0.81–1.19 | 0.86–1.01 | 0.94–1.06 | 0.94–1.06 |
15 | 0.81–1.08 | 0.87–1.16 | 0.89–1.02 | 0.94–1.06 | |||
20 | 0.83–1.10 | 0.88–1.16 | 0.91–1.03 | 0.94–1.06 | |||
1500 | 10 | 0.77–1.02 | 0.87–1.14 | 0.84–1.15 | 0.87–1.00 | 0.95–1.05 | 0.95–1.05 |
15 | 0.82–1.05 | 0.89–1.13 | 0.90–1.01 | 0.95–1.05 | |||
20 | 0.85–1.07 | 0.89–1.13 | 0.92–1.02 | 0.95–1.05 | |||
2000 | 10 | 0.75–1.04 | 0.89–1.12 | 0.86–1.13 | 0.87–0.99 | 0.96–1.05 | 0.96–1.04 |
15 | 0.84–1.04 | 0.89–1.13 | 0.91–1.01 | 0.96–1.04 | |||
20 | 0.86–1.05 | 0.91–1.11 | 0.92–1.02 | 0.96–1.04 | |||
3000 | 10 | 0.81–0.99 | 0.91–1.10 | 0.89–1.11 | 0.88–0.99 | 0.96–1.04 | 0.96–1.04 |
15 | 0.85–1.02 | 0.92–1.09 | 0.91–1.00 | 0.97–1.03 | |||
20 | 0.87–1.03 | 0.92–1.09 | 0.93–1.02 | 0.97–1.03 | |||
10 000 | 10 | 0.83–0.97 | 0.95–1.05 | 0.94–1.06 | 0.89–0.97 | 0.98–1.02 | 0.98–1.02 |
15 | 0.88–0.99 | 0.95–1.05 | 0.92–0.99 | 0.98–1.02 | |||
20 | 0.90–1.00 | 0.96–1.05 | 0.94–1.00 | 0.98–1.02 |