[Rasch] Fit & Dimensionality
ici_kalt at yahoo.com
Mon Jul 14 22:52:02 EST 2008
Hello, concerning the paper mentioned in previous messages:
It says that "For data and item pools that fail to fit the Rasch model, various reasons are listed. For instance, the two-parameter logistic or three-parameter logistic models would probably be more suitable."
Do we agree with this? If the item pool fails to fit the Rasch model, then the pool is not really suitable to MEASURE something, why the need to have MORE SUITABLE MODELS (2 and 3 PL), more suitable for what? To FIT (not measure) something?
Please give some insight.
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--- On Mon, 7/14/08, Mike Linacre (RMT) <rmt at rasch.org> wrote:
From: Mike Linacre (RMT) <rmt at rasch.org>
Subject: Re: [Rasch] Fit & Dimensionality
To: rasch at acer.edu.au
Date: Monday, July 14, 2008, 1:03 AM
"Rasch model misfit does not necessarily contradict unidimensionality. The appropriateness of the scoring rule has merely been invalidated in the latter case" (p.381). http://www.informaworld.com/smpp/content~content=a785034366~db=all
Yes, this would happen when an MCQ item has been keyed incorrectly, or a survey item including the word "not" has not been reversed scored. Including different response formats (of different discrimination) in the same instrument can also produce misfit.
And we could imagine other situations in which items operationalizing a unidimensional latent trait would cause the data to misfit the Rasch model. For instance, on an MCQ test, items which cue other items. Or on a survey, items which summarize other items.
When misfit is seriously distorting the measures, the "appropriate scoring rule" could become "Don't score this item!"
How does this sound?
Mike L. _______________________________________________
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