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
Should data for the linear mixed model analysis meet the three assumptions of ANOVA?
3 messages · Junli, David Winsemius, Colstat
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
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