Rating Scale Instrument Quality Criteria

Rating Scale Instrument Quality Criteria
Criterion	Poor	Fair	Good	Very Good	Excellent
Targeting *	> 2 errors	1-2 errors	< 1 error	< .5 error	< .25 error
Item Model Fit Mean-Square Range Extremes	< .33 - >3.0	.34 - 2.9	.5 - 2.0	.71 - 1.4	.77 - 1.3
Person and Item Measurement Reliability	<.67	.67-.80	.81-.90	.91-.94	>.94
Person and Item Strata Separated	2 or less	2-3	3-4	4-5	>5
Ceiling effect: % maximum extreme scores	>5%	2-5%	1-2%	.5-1%	<.5%
Floor effect: % minimum extreme scores	>5%	2-5%	1-2%	.5-1%	<.5%
Variance in data explained by measures**	??	??	??	??	??
Unexplained variance in contrasts 1-5 of PCA of residuals	>15%	10-15%	5-10%	3-5%	<3%
This Table has been developed by William P. Fisher, Jr. based on the Rasch literature and his many years of experience conducting Rasch analyses in different settings.

Criterion

Poor

Fair

Good

Very Good

Excellent

Targeting *

> 2 errors

1-2 errors

< 1 error

< .5 error

< .25 error

Item Model Fit Mean-Square Range Extremes

< .33 - >3.0

.34 - 2.9

.5 - 2.0

.71 - 1.4

.77 - 1.3

Person and Item Measurement Reliability

<.67

.67-.80

.81-.90

.91-.94

>.94

Person and Item Strata Separated

2 or less

2-3

3-4

4-5

Ceiling effect: % maximum extreme scores

>5%

2-5%

1-2%

.5-1%

<.5%

Floor effect: % minimum extreme scores

>5%

2-5%

1-2%

.5-1%

<.5%

Variance in data explained by measures**

Unexplained variance in contrasts 1-5 of PCA of residuals

>15%

10-15%

5-10%

3-5%

<3%

This Table has been developed by William P. Fisher, Jr. based on the Rasch literature and his many years of experience conducting Rasch analyses in different settings.

* 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:

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%.

Rasch Publications
Rasch Measurement Transactions (free, online)	Rasch Measurement research papers (free, online)	Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch	Applying the Rasch Model 3rd. Ed., Bond & Fox	Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters	Introduction to Rasch Measurement, E. Smith & R. Smith	Introduction to Many-Facet Rasch Measurement, Thomas Eckes	Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.	Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar	Journal of Applied Measurement	Rasch models for measurement, David Andrich	Constructing Measures, Mark Wilson	Rasch Analysis in the Human Sciences, Boone, Stave, Yale
in Spanish:	Análisis de Rasch para todos, Agustín Tristán	Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

Rasch Publications

Rasch Measurement Transactions (free, online)

Rasch Measurement research papers (free, online)

Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch

Applying the Rasch Model 3rd. Ed., Bond & Fox

Best Test Design, Wright & Stone

Rating Scale Analysis, Wright & Masters

Introduction to Rasch Measurement, E. Smith & R. Smith

Introduction to Many-Facet Rasch Measurement, Thomas Eckes

Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.

Statistical Analyses for Language Testers, Rita Green

Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar

Journal of Applied Measurement

Rasch models for measurement, David Andrich

Constructing Measures, Mark Wilson

Rasch Analysis in the Human Sciences, Boone, Stave, Yale

in Spanish:

Análisis de Rasch para todos, Agustín Tristán

Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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Go to Institute for Objective Measurement Home Page. The Rasch Measurement SIG (AERA) thanks the Institute for Objective Measurement for inviting the publication of Rasch Measurement Transactions on the Institute's website, www.rasch.org.

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