lamjas posted on Thursday, January 10, 2013 - 8:10 am
I am using TIMSS database and want to do a SEM (e.g., X --> M --> Y).
Y is achievement. In the dataset, however, achievement is represented by five plausible values (say pv1, pv2, pv3, pv4, pv5). I understand that they should not be treated as indicators in the model. I read some threads and it seems that I need to do "multiple imputation" (In Mplus, using Type = Imputation).
However, I am still very confused the appropriate procedures to deal with a SEM model with plausible values as an outcome variable. Could anyone explain step by step in layman terms? Is UG Ex 11.7 exactly the way I use imply on my model (of course, I need to change from LGM to SEM)?
One simple approach is to let "FIML" handle that without imputation.
Huang Wu posted on Saturday, June 09, 2018 - 3:32 pm
I am using PISA data for analysis. These discussions are very helpful but I am still have some questions. (1) I could not find "FIML" in the estimator; (2) PISA give us 10 plausible value for each subject. Should us create 10 dataset first (each one only have one plausible value for different subject?) or just keep them in a dataset and treated them as indicators? (3) I have read lamjas's post and he/she said we could not treat plausible as indicator but in his/her code, he/she load 5 plausible value in y. If one dataset only contains one plausible value, how can we load them together? Thanks