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 Clio Berry posted on Tuesday, July 17, 2012 - 8:29 am
Another question:

I have variables which are non-normal so assume I should either transform them or use WLSMV estimation.

Many of the variables have univariate outliers (based on z scores >3, should I do something about the outliers by either removing cases, transforming the scores or transforming the variables as well as using WLSMV? Or should I just use WLSMV and leave the scores as they are?

Thank you,

Clio.
 Linda K. Muthen posted on Tuesday, July 17, 2012 - 5:06 pm
When you say non-normal, do you mean continuous variables that are not normally distributed or categorical variables?
 Clio Berry posted on Wednesday, July 18, 2012 - 7:08 am
Apologies, I mean continuous variables that are not normally distritbuted, i.e. some are negatively skewed, some are positvely skewed and one is negatively skewed/approaching bimodal.
 Linda K. Muthen posted on Wednesday, July 18, 2012 - 12:13 pm
You should treat the outliers in the regular way and use MLR.
 Clio Berry posted on Friday, July 20, 2012 - 2:10 pm
Thank you.

And what if I have one categorical (ordered) variable and other continuous non-normal variables?

Should I then use WLSMV? Should I still transform univariate outliers if using WLSMV?

Thank you,

Clio.
 Linda K. Muthen posted on Friday, July 20, 2012 - 4:38 pm
MLR is better for non-normal continuous variables. I would treat outliers the same with any estimator.
 Clio Berry posted on Friday, July 27, 2012 - 1:16 pm
Thank you for your reply.
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