Help : glm p-values for a factor predictor
It might help if you provided the code you used. It's possible that you didn't use direction="backward" in stepAIC(). Or if you did, it was still running, so whatever else you try will still be slow. The statement "R provides only the pvalues for each level" is wrong: look at the anova() function. Bob
On 29 June 2017 at 11:13, Beno?t PELE <benoit.pele at acoss.fr> wrote:
Hello,
i am a newby on R and i am trying to make a backward selection on a
binomial-logit glm on a large dataset (69000 lines for 145 predictors).
After 3 days working, the stepAIC function did not terminate. I do not
know if that is normal but i would like to try computing a "homemade"
backward with a repeated glm ; at each step, the predictor with the max
pvalue would be excluded until reaching a set of 20 predictors for
example.
My question is about the factor predictors with several levels. R provides
only the pvalues for each level whereas i need an overall pvalue for
testing the predictor.
On internet, the only solution i found suggests to compute a Khi2
log-likelihood test between the complete model and the model without the
factor predictor to emphasize its relevance.
Do you know other ways? Another R package managing this kind of issue?
Thank you and best regards, Benoit.
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