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Re: st: REML with non-normally distributed dependent Variable


From   Christian Weiss <christian.weiss@nightberry.de>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: REML with non-normally distributed dependent Variable
Date   Wed, 3 Jun 2009 16:32:11 +0200

Hello!

as initially mentioned I am using the variable as dependent variable
for a random intercept model estimaed with REML (using xtmixed).
Afaik univariate normal-distribution is one of the prerequesits for
multivariate normality which is one of the assumptions for ML
estimators?!

Best regards
Chris



On Wed, Jun 3, 2009 at 4:19 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> In absolute terms the fit looks pretty lousy to me! However, that may
> not matter at all. You are looking at the marginal distribution of the
> response. Where does it say that matters for that what you have in mind?
>
>
> Nick
> n.j.cox@durham.ac.uk
>
> Christian Weiss
>
> Thank you for your answer!
>
> I already log-transformed the variable, yielding the following result:
>
> http://yfrog.com/11graphpp
>
> ...looks relatively normally distributed to me.
>
> Unfortunately, swilk and swfrancia still tell me that it's not
> normally distributed...
>
> On Tue, Jun 2, 2009 at 10:04 PM, Dan MacNulty <macn0007@umn.edu> wrote:
>> Why not transform your dependent variable (e.g, log-transform) to
>> approximate a normal distribution? Dan
>>
>> Christian Weiss wrote:
>
>>> I am working with a random-intercept model using REML. As it turned
>>> out my dependent variable is not normally distributed.
>>> If I recall it correctly, one of the assumptions of ML is
> multivariate
>>> normality. Do you have any advice what to do or to consider?
>
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