"I would suggest rethinking your reliance on Rasch fit
statistics as a criterion for item rejection .... In many case, the
best (most highly discriminating) items would be rejected if one
relied on Infit and Outfit statistics."
NCME reviewer, as reported by Ryan Bowles.
Conventional wisdom says "When items correlate highly with one another, those with the highest average correlations are the best items" (Jm Nunnally, Psychometric Theory, 1967, p. 261). But it is well-established that there can be too much of a good thing ... inter-item correlations can become too high:
"Other things being equal, interdependent items tend to decrease the reliability of a test. ... For the tendency becomes to answer neither item or both items and thereby produces an effect equivalent to reducing the number of items in a test." (Percival M. Symonds, Factors influencing test reliability, Journal of Educational Psychology, 1928, 19, 73-87. Italics his.)
Rasch Infit and Outfit statistics flag items to which responses are overly predictable, an indication that, in some way, they are interdependent with other items.
Rejecting Best Items? R. Bowles Rasch Measurement Transactions, 2003, 17:1, 917.
|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|
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