st: glm model syntax

[Nikolaos Pandis <npandis@yahoo.com>]

Hi to all.
 
I have a continuous dependent variable and 4 predictors.
 
The depedent variable is aproximately normally distributed, however, using the -ladder- command it is indicated that if I use the inverse (1/dep_var) my data will approximate normal distribution better compared to using the untransformed data.
 
If I fit a glm model is the syntax below correct?

xi:glm dep_var i.var1 i.var2 var3 var4,link(power -1)
 
The other question is whether for the dep_var I would need to use the inverse of the dep_var or the untransformed dep_var?
 From my experiment below it seems to me that I should use the inverse of the dep_var unless my model (link function) is not correctly specified? I thought that I should use the dependent variable untransformed an the link function will take care of the rest?
 
If I compare:
 
1. xi:glm dep_var i.var1 i.var2 var3 var4,link(power -1)

2. xi:glm invesre_dep_var i.var1 i.var2 var3 var4,link(power -1)
 
3. xi:glm dep_var i.var1 i.var2 var3 var4
 
models 2 and 3 give very similar results but model 1 very different. 
The difference between model 1 and 2 is the untransformed or the tranformed dependent variable. 
Perhaps models 2-3 are the same. Are the results form 2 & 3 similar because the data is close to normal anyways or is it because the specified models are equivalent. 
If models are equivalent then the very large difference in the coefficients between 1-2 do no make sense to me.
 
I looked at the help glm file but I was not able to figure this out.
 
Any comments would be appreciated.
 
Thank you,
 
Nick

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