Skip to Content

likelihood ratio test in R

I'm not sure if I'm asking something stupid or off topic here, but I can't think where can I ask this question.

suppose I am going to do a univariate logistic regression on several independent variables, like this:

mod.a <- glm(x ~ a, data=z, family=binominal("logistic"))
mod.b <- glm(x ~ b, data=z, family=binominal("logistic"))

I did a model comparison (likelihood ratio test) to see if the model is better than the null model by this command

1-pchisq(mod.a$null.deviance-mod.a$deviance, mod.a$df.null-mod.a$df.residual)

Then I built another model with all variables in it

mod.c <- glm(x ~ a+b, data=z, family=binomial("logistic"))

In order to see if the variable is statistically significant in the multivariate model, I used the lrtest command from epicalc

lrtest(mod.c,mod.a) ### see if variable b is statistically significant after adjustment of a
lrtest(mod.c,mod.b) ### see if variable a is statistically significant after adjustment of b

I wonder if the pchisq method and the lrtest method are equivalent for doing loglikelihood test? As I dunno how to use lrtest for univate logistic model.

(Please kindly let me know if I asked the wrong question here, thanks!)