Rating Scale Instrument Quality Criteria

* How far the average or modal measure is from the center of the item calibrations. Just as a rough indication, if the average measure is less than one error of measurement from the center of the item hierarchy, then the instrument is on target. The average individual error of measurement made more sense to me to use than the SE of the mean, as this latter can be quite small. Of course, an instrument might not have items that go as far up or down the scale as the measures go, so some indication of how well the measure and calibration distributions match would also be in order.

** The variance explained by the measures in a Principal Components Analysis of the standardized residuals changes with the targeting of the items on the persons. There is no set range of values useful for assessing scale functioning. For more information, see:

• Linacre, J. M. (2003, Winter). PCA: Data variance: Explained, modeled and empirical. Rasch Measurement Transactions, 17(3), 942-943.
• Linacre, J. M. (2006). Data variance explained by Rasch measures. Rasch Measurement Transactions, 20(1), 1045.
• Linacre, J. M. (2008). PCA: Variance in data explained by Rasch measures. Rasch Measurement Transactions, 22(1), 1164.

Rating Scale Instrument Quality Criteria. Fisher, W.P. Jr. … Rasch Measurement Transactions, 2007, 21:1 p. 1095

This article was revised by Fisher, W.P. Jr. on 2/1/2018. The original table showed the Variance in data explained by measures as: <50%, 50-60%, 60-70%, 70-80%, and >80%.

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