[Rasch] Validity in Rasch
S.Kreiner at biostat.ku.dk
Fri Mar 25 21:57:50 EST 2011
I agree completely with Mike's classification. Statistically
unacceptable fit may indicate that there can be a measurement problem,
but not that there actually is a problem. I would say, that we have a
substantially-good-enough fit if measurement is robust to the model
errors. If there, for instance, is DIF for one out of 30 items I would
expect that measurement by the Rasch model is relatively robust. If
there is DIF among 20 out of 30 items, I would expect that measurement
is not robust. In both cases, however, I would attempt to assess the
robustness of measurement to the misfit before I decide what to
conclude. I would never assume that my expectations are correct.
Concerning overfitting data, e.g. data where infits are much closer to 1
than expected by the random component of Rasch models, I would in most
cases do the same as Mike. It happens, but not very often.
Den 24-03-2011 06:02, Mike Linacre skrev:
> Svend writes: What we may disagree about is what to do when items do
> not fit the model.
> Here, an extra category of fit of the data to the model is helpful:
> 1. Statistically-acceptable fit
> 2. Substantively-good-enough fit
> 3. Unacceptable fit
> The criteria for good-enough fit depend on the situation in the same
> way as industrial-quality-control tolerance limits depend on their
> situation. So, before rejecting an item (or a person, a rater, ...),
> we need to decide "what amount of misfit is acceptable?" For instance,
> in rated performances, we may decide that observations that overfit
> the Rasch model (too predictable) are always acceptable.
> Mike L.
> Mike Linacre
> Editor, Rasch Measurement Transactions
> rmt at rasch.org _www.rasch.org/rmt/_ <http://www.rasch.org/rmt/> Latest
> RMT: 24:4 Spring 2011
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