To whom it may concern,

I try to calculate a multilevel model for the effect of migration integration policy index (MIPEX) on the individual attitudes toward immigrant across 19 European countries. My dependent variable is an index of seven variables on a 10-point likert scale. All seven variables are uniquely coded and I uses Cronbach's alpha (= 0.86) to from this index. Everything worked so far.

alpha imueclt imwbcnt imtcjob imbleco imwbcrm rlgueim imbgeco, gen(attitudes)
label variable attitudes "Attitudes towards immigrants, higher values meaning more pos. attitudes"

But if want to run an empty multilevel model, the second and concurrent last iteration is backed up. What seems really weird to me, because I have no idea why already the empty model failed to reach convergence. Hence, the problem must be my dependent variable or the country variable?

mixed attitudes || country:, var

My question now is, how can I solve this problem? Without convergence I don't get reliable results.

Thanks in advance for every answer.

Best,
Emely