Jackknife in logistic regression

Question

I'm interested into apply a Jackknife analysis to in order to quantify the uncertainty of my coefficients estimated by the logistic regression. I´m using a glm(family=’binomial’) because my independent variable is in 0 - 1 format.

My dataset has 76000 obs, and I'm using 7 independent variables plus an offset. The idea involves to split the data in let’s say 5 random subsets and then obtaining the 7 estimated parameters by dropping one subset at a time from the dataset. Then I can estimate uncertainty of the parameters.

I understand the procedure but I'm unable to do it in R.

This is the model that I'm fitting:

glm(f_ocur ~ altitud + UTM_X + UTM_Y + j_sin + j_cos + temp_res + pp +
             offset(log(1/off)), data = mydata, family = 'binomial')

Does anyone have an idea of how can I make this possible?