Computation of OUTFIT and INFIT Statistics


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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