Re: st: Mixed effects model for asymmetric data

[Ana Beatriz FS <nutrianabeatriz@gmail.com>]

Thanks,  JVVerkuilen,

Unfortunately my variable is not a count one, I work with levels of hormones.

Following your suggestion, I assessed the quality of the model by the
residuals and it's really really bad.

With respect to the transformations, they produce quite different
distributions. I haven't find one that would fit all my points in
time, even if not perfectly. I do think I have a problem here!

Best regards,

Ana Beatriz


2012/9/26 JVerkuilen (Gmail) <jvverkuilen@gmail.com>:
> On Wed, Sep 26, 2012 at 1:13 PM, Ana Beatriz FS
> <nutrianabeatriz@gmail.com> wrote:
>> Dear Statalisters,
>>
>> I was performing multilevel mixed-effects linear regression but I
>> realized my data is not normally distributed. Is there an equivalent
>> model for asymmetric data in stata?
>>
>> I've tried to transform my data but I could not accomplish because my
>> data require different transformations in each point of follow-up. My
>> sample is composed by pregnant women in the three trimesters of
>> pregnancy, but values of my dependent variable in first trimester
>> require log transformation for normalization, in the second, sqrt
>> transformation and so on.
>
> What are the measures? For instance, if they are counts, you might be
> better off with -xtmepoisson-, which assumes that you have multilevel
> Poisson distributed data. If the transformations are all fairly close,
> you can probably get away with choosing one, so if the right answer is
> sqrt and you log instead it won't be *that* far off. Also keep in mind
> that the marginal distribution before conditioning on regressors can
> be rather far from normal, so it's not really clear you need to do any
> transformation. What do the residuals look like?
>
>
> --
> JVVerkuilen, PhD
> jvverkuilen@gmail.com
>
> "Out beyond ideas of wrong-doing and right-doing there is a field.
> I'll meet you there. When the soul lies down in that grass the world
> is too full to talk about." ---Rumi
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