[R] Using item difficulties from a fitted Partial Credit Model to predict person abilities in an extended dataset?
dw|n@em|u@ @end|ng |rom comc@@t@net
Sun Jun 7 20:48:49 CEST 2020
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On 6/7/20 8:31 AM, Rob Forsyth wrote:
> OK thanks for the guidance
>> On 7 Jun 2020, at 16:15, Bert Gunter <bgunter.4567 using gmail.com> wrote:
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>> Such package/methodology specific questions may well go unanswered here. They are essentially offtopic anyway: this list is about general R programming questions and cannot be expected to support the ~ 20000 packages now in the ecosystem. I suggest that you contact the package maintainer (?maintainer) for help or to find out what support resources may be available.
>> Bert Gunter
>> "The trouble with having an open mind is that people keep coming along and sticking things into it."
>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>> On Sun, Jun 7, 2020 at 3:59 AM Rob Forsyth <rob.forsyth using newcastle.ac.uk> wrote:
>> I am using the eRm package to examine the properties of a clinical rating scale using a Partial Credit Model (PCM). I understand how to extract the person ability estimates (thetas) from a simple fitted PCM but I have a dataset with repeated observations over time (~1200 observations of the instrument in ~250 individuals). So as not to violate assumptions of conditional independence I've fitted the PCM to single observations drawn at random from each subject. This works but I would now like to use the item diffculty estimates from the fitted PCM to generate person-ability estimates for the remaining ~950 observations (at other timepoints) not used to fit the model; and I can't see from the eRm package documentation how to do this?
>> Advice very much appreciated
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