Hi Elisabeth,
I'm certainly no expert here, but you could try using pql2 instead. Either way, you should probably follow each model by an MCMC run using the initsprevious option. e.g.
runmlwin Kess_bin cons E_D E_E W_A W_D S_A S_D NI_A NI_D hiinc_lowocc hiocc_lowinc gm_age, level3(mcsid: cons ...
Search found 2 matches
- Wed Aug 19, 2015 5:15 pm
- Forum: runmlwin user forum
- Topic: Logistic growth curve model problem
- Replies: 2
- Views: 5072
- Wed Aug 19, 2015 3:02 pm
- Forum: runmlwin user forum
- Topic: Parameter expansion introducing bias?
- Replies: 1
- Views: 4790
Parameter expansion introducing bias?
Hi all. I'm not sure if I can get my question across in an understandable way, so please tell me if I'm making no sense!
I'm running a 3-level logistic model with a single binary outcome via runmlwin. Nicely-sized dataset. No cross-classification. Binary observations occur at regular intervals but ...
I'm running a 3-level logistic model with a single binary outcome via runmlwin. Nicely-sized dataset. No cross-classification. Binary observations occur at regular intervals but ...