I am trying to replicate a Stata xtlogit re regression that is run on panel data in R. By panel data I mean that I have multiple observations for different individuals (person_id) in different years (year_id). My dependent variable (DV) is binary. I have 2 main variables of interest that I want to predict (IV1 & IV2) and a number of control variables (some_controls). In total I have about 40.000 observations.
I am a novice in using Stata, so I might just have failed to identify relevant parts of the code that feed into the xtlogit command. However, as far as I could see the relevant Stata code is as follows:
isid person_id year_id
xtset person_id year_id,y
eststo: xtlogit DV IV1 IV2 some_controls cformat(%3.2f) pformat(%3.2f) re vsquish noomitted nolog noemptycells vce(robust)
I tried replicating this in R using the following formulas:
using the "plm" package:
plm(DV ~ IV1 + IV2 + some_controls, index = c("person_id","year_id"), model ="random", data = data_frame_name)
using the lme4 package:
glmer(DV ~ IV1 + IV2 + some_controls + (1|person_id) + (1|year_id), family = binomial, data = data_frame_name)
Unfortunately, the plm model fails to reproduce the results I get by running the Stata code. The glmer model returns the error "Error: pwrssUpdate did not converge in (maxit) iterations".
I would be thankful for suggestions on how to replicate the results calculated by the Stata code exactly.
I have found Stata's xtlogit (fe, re) equivalent in R?. However, I'm not sure how the solution to that question would be applied to panel data.