[R] data distribution for lme

[Rolf Turner]

See inline below.

On 12/11/13 11:28, Bert Gunter wrote:
> This is not really an R question -- it is statistics.
> In any case, you should do better posting this on the
> R-Sig-Mixed-Models list, which concerns itself with matters like this.
>
> However, I'll hazard a guess at an answer: maybe.  (Vague questions
> elicit vague answers).

No! Nay! Never!  Well, hardly ever.   The ***y*** values will rarely be 
Gaussian.
(Think about a simple one-way anova, with 3 levels, and N(0,sigma^2) errors.
The y values will have a distribution which is a mixture of 3 
independent Gaussian
distributions.)

You *may* wish to worry about whether the ***errors*** have a Gaussian
distribution.  Some inferential results depend on this, but in many cases
these results are quite robust to non-Gaussianity.

There.  I have exhausted my knowledge of the subject.

     cheers,

     Rolf
>
> Cheers,
> Bert
>
> On Tue, Dec 10, 2013 at 6:55 AM, peyman <zirak.p at gmail.com> wrote:
>> Hi folks,
>>
>> I am using the lme package of R, and am wondering if it is assumed that
>> the dependent factor (what we fit for; y in many relevant texts) has to
>> have a normal Gaussian distribution? Is there any margins where some
>> skewness in the data is accepted and how within R itself one could check
>> distribution of the data?