Hi Hanne
I have submitted the command file below and it runs without errors. However, it does not seem to converge to a good solution. I have added a command that exports a log file in which you can see that the deviance is jumping up and down between iterations, instead of slowly becoming smaller. When you look at the maximum change in item parameter estimates, you can see that these stay large until the last iteration and are not converging to your criterion of 0.05. Sometime the problem is just one skewed item or a bad fitting item, but in your case several items keep changing between iteration.
This often happens for models with many (about 6 or more) dimension, especially -- as in your case -- when you have a small sample and only few items per dimension. You probably need to simplify your model to make it converge to a good solution. Have a look if there are any bad fitting items that you can delete and decrease the number of dimension. You could also try to run two separate models with only part of the items and dimensions.
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title 12dim;
datafile 12dim.sav !filetype=spss, responses=q1 to q47;
codes 1,2,3,4;
score (1,2,3,4) (0,1,2,3) () () () () () () () () () () () ! items (1-4);
score (1,2,3,4) () (0,1,2,3) () () () () () () () () () () ! items (5-8);
score (1,2,3,4) () () (0,1,2,3) () () () () () () () () () ! items (9-12);
score (1,2,3,4) () () () (0,1,2,3) () () () () () () () () ! items (13-16);
score (1,2,3,4) () () () () (0,1,2,3) () () () () () () () ! items (17-20);
score (1,2,3,4) () () () () () (0,1,2,3) () () () () () () ! items (21-23);
score (1,2,3,4) () () () () () () (0,1,2,3) () () () () () ! items (24-28);
score (1,2,3,4) () () () () () () () (0,1,2,3) () () () () ! items (29-31);
score (1,2,3,4) () () () () () () () () (0,1,2,3) () () () ! items (32-36);
score (1,2,3,4) () () () () () () () () () (0,1,2,3) () () ! items (37-40);
score (1,2,3,4) () () () () () () () () () () (0,1,2,3) () ! items (41-43);
score (1,2,3,4) () () () () () () () () () () () (0,1,2,3) ! items (44-47);
set constraints=cases;
export logfile >> 12dim.log;
model item+item*step;
export parameters >> 12dim.prm;
export reg_coefficients >> 12dim.reg;
export covariance >> 12dim.cov;
import init_parameters << 12dim.prm;
import init_reg_coefficients << 12dim.reg;
import init_covariance << 12dim.cov;
estimate!method=montecarlo,nodes=2000,converge=.005, stderr=quick,iter=1000;
show !tables=1:2:3:4:5,estimates=latent >>12dim.shw;
/* note that next command will produce many warnings because of so few items per dimension */
show cases !pfit=yes,estimates=wle,filetype=xls>> 12dim_PersonFit12dim.xls;
show !filetype=xls, estimates=mle,tables=1:2:3:4 >> 12dim_ItemFit12dim.xls;
itanal >> 12dim_tradAnalyses12dim.xls;
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Please let me know if you need any further assistance.
Eveline