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I have a panel dataset (covering 3 periods), in which we've stacked the data so that each individual respondent has 4-8 observations. The independent and dependent variables are both on a Likert scale. My general idea is: dependent = indep1 + gend + indep1*gend, with fixed effects.

I found this paper that seems to do a similar thing (ordinal logistic regression with fixed effects, feologit in Stata). I'm basically just wondering whether this still works for stacked data?

My dataset looks like this:

Resp  depen Indep1  gend
 1       1      1   f
 1       2      2   m
 1       4      3   f
 2       2      4   f
 2       4      1   m
 3       3      2   f

A paper did a similar thing to what I intend to do and used alternative specific multinomial probit - but I have the Likert scale outcome, more time periods and I'd rather not estimate separate models for the gender (gend).

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This is probably a place for a proportional odds ordinal logistic model with random effects (random intercepts) for subjects. See for example the R mixor package or the R rmsb package.

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