[Rasch] Modeling response time

Ricardo Primi rprimi at mac.com
Sat Feb 4 00:26:49 AEDT 2017

Glad that worked !

Just a correction of a mistake on my last post: in DIF you have several people on the same group (not items as was originally written) and them you have a interaction parameter that indicates the change in main effect of item difficulty due of being a person of group X. So in these case you have several data points (people in the group) for the interaction affect to be identifiable 

greetings from Brazil

> Em 2 de fev de 2017, à(s) 17:55, Stuart Luppescu <lupp at uchicago.edu> escreveu:
> On Tue, 2017-01-31 at 19:00 -0200, Ricardo Primi wrote:
>> Hi Stuart
>> I guess that you don’t want to model interaction . You want to model
>> main effects of item and person to and then inspect the residuals
>> trying to see who is far off the predicted RT from 
>> this model considering additive main effects  right? Besides
>> including interaction make this model  non-identified because you
>> have an interaction parameter for each combination of personX item
>> (minos 1)
>> Usually IRT models are just main effects models (person as a random
>> variable and item as fixed or sometimes random variables).
>> Interactions are used to assess DIF. In this case you have several
>> items from the same group and this makes the identification of
>> interaction possible (you have the same interaction parameter for th
>> items of the same group)
>> So i think the model would be :
>> lmer(log(answer_time) ~ qid + (1|examinee), data=test.DF, REML=FALSE)
>> And then examine the residuals after fitting this model
> This worked great! Thanks very much, Ricardo.
> -- 
> Stuart Luppescu
> Chief Psychometrician (ret.)
> UChicago Consortium on School Research
> http://consortium.uchicago.edu
> lupp at uchicago.edu
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