Hello there!
I have a data of residual milk of cows and in this data have a lot of zeros, meaning that the cow haven't any milk retained in the udder.
I am using PROC GLM to analyse milk production and residual milk, as recommended.
But in this specific data, the model (too high) and R square (too low) is not good at all because the number of information with zero as observed result.
I can't delete this information, aren't outliers...
How I can manege that??
Thank you!
Aska.
Try to use distribution GAMMA or TWEETIE to fit model ,better use TWEETIE distribution.
Hello Ksharp, thank you for your help.
My procedure is like this, how can I fit the distribution?
PROC GLM (or should be mixed?);
CLASS treatment po dl cow;
MODEL residual= treatment po dl treatment*po treatment*dl;
lsmeans treatment//pdiff stderr lines;
lsmeans treatment*op1/pdiff stderr lines;
RUN;
I have repeated measures of each cow by day of lactation (dl)
po is the parturition order (primiparous or multiparous)
Thank you.
Aska.
I am not sure.
PROC GENMOD;
CLASS treatment po dl cow;
MODEL residual= treatment po dl treatment*po treatment*dl /dist=gamma ; /*or dist=tweetie*/
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