Dear R friends

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?

I´d really appreciate if someone could help me with this.

Thank you in advance.

P.S. More information can be added if needed.

Best regards.

Lucas.

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