Thanks to Pablo, Guilaume, and Stephen for your posts—all very helpful.
By way of providing some background (per request from the list moderator), I
am in the process of developing an iterative approach to detecting drift in
item parameters over time within the context of an item response theory
(IRT) model. Given two or more time points, model 1 estimates person
measures (thetas) for all ¬¬respondents based on their responses to a set of
questions. Model 2 estimates time-specific item difficulties, using the
thetas estimated in model 1. The cut() function is useful here as I do not
want to have model 2 influence or change the estimates of the thetas
produced by model 1.
Thanks again
Barth
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