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
system limit exceededOkay, so I have Stata version 16.0 and is running a firm-level innovation data of Zimbabwe. I have t…
Very high numbers when holding time fixed in regressionHi everyone, I am not sure if this is a coding question or not, but maybe I do something wrong when…
DateI am trying to generate a date in my work. I am only working with year intermissions between dates f…
R-sqaured in multilevel analysisHi! For multilevel analysis, do you recommend to use AIC instead of mltrsq (Snijders-Bosker R-Square…
Using replace produces wrong resultDear all, I have this simplified dataset Code: * Example generated by -dataex-. To install: ssc in…
Subscribe to:
Post Comments (Atom)
0 Response to Variables selection methods , minimum number of variables - max information
Post a Comment