I'm still waiting on my 64-bit OS upgrade, so meanwhile I'm fighting a lot of memory battles.
I'm running a difficult model with numeric integration (5^4 points) on imputed data.
The first dataset seems to run normally, but the second one runs out of memory. Is this likely to be a quirk of the second dataset, or does the memory requirement of the problem cumulate across datasets?
I am trying to impute my data for multiple group analysis (n=2016). There are missing values on x and y variables. The y variables are categorical, the x variables are continuous or dummy-coded. In the syntax i do not declare the y variables as categorical, but use the option „values“ to assign their values. The imputation runs fine. But when I try to impute using the grouping option in addition, i get the error message „THERE IS NOT ENOUGH MEMORY SPACE TO RUN Mplus ON THE CURRENT INPUT FILE...“. Is there anything wrong with my syntax or it’s only a memory space problem? What would you suggest to solve this problem? Would it be a too rough approximation to leave out the option "grouping" when doing the imputation and instead use it on the second step with the already imputed data? I very much appreciate your help.
Variable: NAMES ARE ....; MISSING ARE all (-99); GROUPING IS REGION (1=OST 2=WEST);
The way you have your input set up, all variables on the NAMES list will be used to impute the data. Please see the latest Topic 9 course handout where there is a newer example of how to use NAMES and USEVARIABLES options with imputation. If this does not help, send the relevant files and your license number to email@example.com.