Good morning to everyone,
I am trying to run a SEM with more levels: the fact is that it is very heavy and I would like to reduce variables in the best possible way.
For now, as I have a lot of variables which explain one dimension, I simply try to look at the significance of coefficients and the increase of R2 (in normal regression) contributed by each individual regressor.
I was wondering if there is a more precise/sophisticated methodology (inside or outside SEM) ?
Many thanks in advance for your time,
wishing you all a great weekend ahead!
Related Posts with Variables selection methods , minimum number of variables - max information
Drop observation in panel dataHi Stata Forum, I have a rather basic question on dropping observation that I cannot seems to solve…
Frequency tableI have monthly data from investment funds over 50 years and would like to have a table showing me ho…
Conditional ttest command in StataDear colleagues. What is the appropriate Stata command to test for the assumption below? Array Tha…
Expanding a dataset with linear interpolationDear Statalist users, I am a new member and I am really glad for being here! I have a monthly pane…
Unexpected behaviour from $frame test: brI am thouroughly thrilled about the new -frame- concept in Stata 16, and I have been using it extens…
Subscribe to:
Post Comments (Atom)
0 Response to Variables selection methods , minimum number of variables - max information
Post a Comment