Ahn,Taeyong posted on Monday, August 21, 2017 - 10:28 am
I was looking for a way to save the class probabilities for an LCA model with multiply imputed datasets. This is the syntax for the analysis with the imputation. I got the error message. What should I do? please help me. :
DATA: FILE IS "C:\Users\사용자\Desktop\XY6281Z\missimplist.dat"; TYPE = IMPUTATION;
SAVEDATA: file is "C:\Users\사용자\Desktop\XY6281Z" ; save = class0ut; *** WARNING in SAVEDATA command The FILE option is not available for TYPE=MONTECARLO or TYPE=IMPUTATION. The FILE option will be ignored. *** WARNING in SAVEDATA command The SAVE option is not available for TYPE=MONTECARLO or TYPE=IMPUTATION. The SAVE option will be ignored. *** ERROR Invalid symbol in data file: "*" at record #: 999, field #: 17
You have to do the savedata for one imputed data set at a time.
Note also that the error message at the bottom indicates that you have * as missing data in the imputed data instead of 999, so say:
Missing = *;
Ahn,Taeyong posted on Monday, August 21, 2017 - 10:48 pm
Thank you for your response. I have done the savedata for one of 10 imputed data sets. Now I am working on the other nine different datasets one by one. Then Are all 10 result files created? So how do i integrate these results?
Ahn,Taeyong posted on Tuesday, August 22, 2017 - 8:25 am
I was told that instead of integrating the results, I had to use the user-specified start value. And I have heard that I can get value by adding something to the MODEL statement from the analysis of one of the imputed datasets. Could you show me what the code looks like?
Ahn,Taeyong posted on Wednesday, August 23, 2017 - 9:46 am
I am doing manual 3-step of GMM with Type=Imputation (I am using 10 sets of multiplely imputed data).I've got the 3 class model in step 1. Now I'm wondering (1) how to get class assignment. As far as I understand, I need to obtain 10 sets of data file that contains class assignment information from each of the 10 sets of imputed data. And then I need to do step 3 with the 10 datasets from step 2. Now I'm also wondering (2) how to integrate the 10 sets of data. I am new at Mplus. I feel it's not easy to tell you about what I want. Do you understand what I mean? Could you help me, please.
(2) 3-step with imputed data is not a situation that is investigated as far as I know. Just one complication is that the class ordering may shift over the different imputation runs. Therefore I would say it is not a suitable topic for a beginner. I would suggest handling missing data differently than using multiple imputation, e.g. by standard ML under MAR.