Reproduced from Rating Scale Analysis
(Wright BD & Masters GN, Chicago, MESA Press, 1982, p.100) with permission
|
Reproduced from Rating Scale Analysis (Wright BD & Masters GN, Chicago, MESA Press, 1982, p.100) with permission |
Page 100 of Rating Scale Analysis (Wright and Masters 1982), which summarizes the calculation of outfit and infit statistics, is reprinted opposite.
Outfit is based on a sum of squared standardized residuals. Standardized residuals are modeled to approximate a unit normal distribution. Their sum of squares approximates a χ² distribution. Dividing this sum by its degrees of freedom yields a mean-square value, OUTFIT MEANSQ, with expectation 1.0 and range 0 to infinity. Values larger than 1.0 indicate unmodeled noise. Values are on a ratio scale, so that 1.2 indicates 20% excess noise. Values less than 1.0 indicate a lack of stochasticity. A Wilson-Hilferty transformation standardizes the mean-square into its OUTFIT ZSTD value. This approximates a unit-normal distribution.
Infit is an information-weighted form of outfit. The weighting reduces the influence of less informative, low variance, off-target responses. It is also computed in INFIT MEANSQ and INFIT ZSTD forms.
Computation of OUTFIT and INFIT Statistics. Wright BD, Masters GN. … Rasch Measurement Transactions, 1990, 3:4 p.84-5
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