After struggling with this problem for a couple of hours I've decided to resort to the forum. If this is an amateur question, please forgive me!
I am trying to run a 3-level (ordered categorical) model in MLWIN using data from the British Election Study. I have 'wave_num' at level 3, 'id' at level 2 (an identifier for respondents some of whom are observed in multiple waves) and 'n' at level 3 (an identifier for individual observations). Unfortunately, mlwin doesn't seem to be recognising my level 2 units properly. Although there are only 89,797 distinct ids, mlwin is seeing 1 id per observation (358,848) which is wrong for my structure, so I'm pretty sure my results are biased.
I have tried a few things already:
- Checking whether the data are sorted correctly (they do seem to be)
- Rounding id in STATA to exactly 1 before feeding it to mlwin.
- Rounding id in mlwin to integers
- Toggling categorical in mlwin
- feeding in ID as strings instead of numeric
- feeding in a subset of ID codes with the STATA 'int' format - i.e. no decimal points allowed
But none of them have resolved it.
Do you have any suggestions? I'm attaching a sample of the code I use to call runmlwin from STATA, as well as screenshots of the 'names' and 'equations' windows from the mlwin worksheet produced by this call.
Thanks in advance for your help
