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However for the PHQ-9 (Tables 3 and 4) consistently more items were identified as misfitting by t-statistics (infit/outfit t-statistic) than by the equivalent mean square statistics.
Fit statistics - infit and outfit mean square statistics - in the fourth column show the differences in the calibration between expected and observed values.
instances where mean square statistics fell outside this range, in particular exceeding 1.3 (misfit).
instances where mean square statistics fell within the critical (0.7 – 1.3) range (i.e. "fit"), and 2).
The mean square statistics used in the Rasch analysis are moderately insensitive of sample size for polytomous data [ 48].
All of the 33 items fitted to the Rasch model with standardized infit and outfit mean square statistics ZSTD < |1.96|.
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Rasch infit mean-square statistics should fall within.80 ~ 1.20 (Bond & Fox 2007, p. 243).
The items were not removed as the Infit mean-square statistics were acceptable.
The in-fit mean-square statistics for AREALD-30 were all within the desired range of 0.50 - 2.0.
Thus, taking into account the relationship between sample size and significance of mean-square statistics, the authors decided to use the sample size of 300 [ 23].
The manual also says that mean-square statistics in the range 0.5 to 1.5 are desirable, and that those over 2 should be treated with care.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com