Apology for my english writing. Hope I will be clear enough ;)
Hi,
I have repeated measures of weight on some 350 animals. I want to
investigate the effet of two factors, sex and breed, on the growth
curve. For this I am using "proc mixed" of sas, with a given
covariance structure that consider the correlations between the
measurements (specified in a "repeated" statement). Random effects as
pen, litter, sire, are specified in a random statement. I want to
modelise the effect of age on the weigth by a polynomial. How should I
test the effect of the sex and breed and their interaction with the
coefficients associated with the age effect? Should I include all
interactions sequentially and test them with type I sum of square
(sequential)? If so, is there a criteria to select which of the
effect, sex or breed, I should include first?
exemple :
model weight= sex breed sex * breed
age age*sex age*breed
age*age age*age*sex age*age*breed
age*age*age age*age*age*sexe age*age*age*breed
I didn't include the interactions of the age effects with the term
sex*breed. Am I OK to do that simplification?
If at least one interaction between age and sex (or between age and
breed) is significant (per example sex*age2), I consider I should test
the sex effect at different ages (in "proc mixed" per exemple, the
statement : "lsmeans sex/pdiff at age=100" allows to test the sex
effect at 100 days of age). But to do this, should I remove all non
significant interactions from the model?
Thanks.
JR
.
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