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Clio Berry posted on Tuesday, July 17, 2012 - 2:29 am
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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. |
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When you say non-normal, do you mean continuous variables that are not normally distributed or categorical variables? |
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Clio Berry posted on Wednesday, July 18, 2012 - 1:08 am
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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. |
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You should treat the outliers in the regular way and use MLR. |
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Clio Berry posted on Friday, July 20, 2012 - 8:10 am
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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. |
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MLR is better for non-normal continuous variables. I would treat outliers the same with any estimator. |
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Clio Berry posted on Friday, July 27, 2012 - 7:16 am
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Thank you for your reply. |
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