[R] Structural equation modeling in R(lavaan,sem)

[jouba]

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 




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