R help - Dec 2011 - Should data for the linear mixed model analysis meet the three assumptions of ANOVA?

Hi All,

I am doing linear mixed model analysis for my multi-location
experiment using R package "lme4". I just wonder whether I should
check my data first to see whether they meet the three assumptions of
ANOVA, that is, independence, normality and homogeneity. I saw a lot
of examples and the manual of lme4, but no one did data check first.
In my experiment, the assumption of homogeneity usually cannot be met.
I do not know whether it will affect the result a lot or not.

Thanks.

Junli

On Dec 17, 2011, at 9:42 PM, Junli wrote:
> Hi All,
>
> I am doing linear mixed model analysis for my multi-location
> experiment using R package "lme4". I just wonder whether I should
> check my data first to see whether they meet the three assumptions of
> ANOVA, that is, independence,
Independence is not part of the data, but rather is a property that  
arises from the design and conduct of the study.
> normality and homogeneity. I saw a lot
> of examples and the manual of lme4, but no one did data check first.
Perhaps because they know more about regression than you do?
> In my experiment, the assumption of homogeneity usually cannot be met.
> I do not know whether it will affect the result a lot or not.
I'm guessing that you are talking about homogeneity of variances or  
homoschedasticity. I'm wondering how you propose to test that  
assumption _before_ you construct a model? You should refer back to  
your text book to see how this assumption was actually presented. If  
it tells you that one can check for that assumption before the model  
is created, then toss that book in the garbage.

-- 

David Winsemius, MD
West Hartford, CT