[Rasch] computing outfit mean-squares for each rating category in eRm (PCM)
rense.lange at gmail.com
Tue Aug 9 21:54:40 AEST 2016
I wonder why we don’t routinely use training and validation samples, as is standard in AI and Machine Learning - even when there are sufficient data to do so. That is, take part of your sample to fit (“train”) the model, and then use another (disjoint) subset to validate the model. If in this case the differences between models would persist in some meaningful fashion, this might be a good reason to prefer one version over the other. Depending on the application and purpose, one might select specific aspects of overall / local fit.
On Aug 9, 2016, at 12:36 PM, Mike Linacre <mike at winsteps.com> wrote:
you asked: "Should I consider other criteria when choosing between RSM and PCM?"
Please see www.rasch.org/rmt/rmt143k.htm - Comparing "Partial Credit Models" (PCM) and "Rating Scale Models" (RSM)"
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