From: jouba <antrael_at_hotmail.com>

Date: Sun, 27 Mar 2011 12:12:19 -0700 (PDT)

Date: Sun, 27 Mar 2011 12:12:19 -0700 (PDT)

I am a new user of the function sem in package sem and lavaan for structural
equation modeling

1. I don’t know what is the difference between this function and CFA
function, I know that cfa for confirmatory analysis but I don’t know what
is the difference between confirmatory analysis and structural equation
modeling in the package lavaan.

2. I have data that I want to analyse but I have some missing data I must to
impute these missing data and I use this package or there is a method that
can handle missing data (I want to avoid to delete observations where I have
some missing data)

3. I have to use variables that arn’t normally distributed , even if I tried
to do some transformation to theses variables t I cant success to have
normally distributed data , so I decide to work with these data non
normally distributed, my question my result will be ok even if I have non
normally distributd data.

4. If I work with the package ggm for separation d , without latent
variables we will have the same result as SEM function I guess
5. How about when we have the number of observation is small n, and what is
the method to know that we have the minimum of observation required??

Thanks a lot

-- View this message in context: http://r.789695.n4.nabble.com/Structural-equation-modeling-in-R-lavaan-sem-tp3409642p3409642.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Sun 27 Mar 2011 - 21:56:13 GMT

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