Can anyone tell me how the LRT is to be interpreted under the glm
package when using glm for logistic regression with mutiple predictors?
family=binomial("logit"))
drop1(Confidence.glm, test="Chisq")
The summary z-table suggests a direction of the effect, and notably the
large LRT statistics are the significant ones. I am used to thinking of
extremely small LRTs as significant (negative natural logarithms of
LRTs). I must assume that the LRT in *R* is alternative hypothesis over
null hypothesis, rather than the convention I learned of
null/alternative, where a small number (negative logLR) represents
strong evidence and zero/zed evidence is represented by an LR of 1
(logLR = 0). Comments? Am I interpreting this correctly?
J. Michael Menke
University of Arizona
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