The cross-sectional IRT analysis in Stata 14 is quite simple. But what about longitudinal data / repeated measures? I just don't know where to start from. I would really appreciate if somebody can push me into the right direction. If it is not possible with the Stata built-in IRT module then any suggestions what software (except 'R') would be relatively simple to use for the task?
I think that your design is three level: 3 - individuals - level 2: items - level 1 the occasions when the tests were taken . Multilevel models can fits such models where the response is a discrete outcome
Here is a reference to
A REPEATED MEASURES, MULTILEVEL RASCH MODEL WITH APPLICATION TO SELF-REPORTED CRIMINAL BEHAVIOR
http://www.ssicentral.com/hlm/techdocs/NotreDamePaper2c.pdf
Stata through GLLAMM has capabilities for Multilevel IRT models- see
How do I fit multilevel IRT models?
http://www.gllamm.org/faqs/models/irtfitm.html
Mplus also has such facilities
https://www.statmodel.com/irtanalysis.shtml
You said you were not interested in R, but this paper gives good insights as to what you can do with lme4
Estimating the Multilevel Rasch Model: With the lme4 Package
http://core.ac.uk/download/pdf/6303142.pdf
Thank you Kelvyn. I will definitely look at these references. I have nothing against R, but I know my limits. I am MD with pretty basic skills in math and programming. Mplus, on the other hand, could be a little too expensive for me. I am going to try GLLAMM first. Have installed Stata few monts ago and just love it.
Hi -- Chapter four of http://biostat.jhsph.edu/~fdominic/teaching/bio656/software/gllamm.manual.pdf has an example of fitting the Law School Admission Test (LSAT)(Bock and
Lieberman, 1970) using gllamm. http://www.oir.pku.edu.cn/umich/teaching/download/20092/reference/Ch005.pdf has more theory than you could ever want. Matthews, JNS, Altman, DG, Campbell, MJ and Royston, P (1990), Analysis of Serial Measurements in Medical Research, BMJ, 300: 230-235 (also, Matthews, JNS (1993), A Refinement to the Analysis of Serial Data Using Summary Measures, Statistics in Medicine, 12: 27-37) are good cites. http://www.stata.com/meeting/1nasug/goldstein.pdf describes using the Rogosa/Saner procedure to do something like what you're talking about, although that may be more complex than what you're seeking to do. In any event, I'm sure glamm will do what you want.