How can I calculate marginal effects from a binomial logistic model with clustered standard errors in R studio?

Asked Jan 12 '22 at 13:08

Active Jan 12 '22 at 13:25

Viewed 95 times

I would like to calculate marginal effects for this logistic model with clustered standard errors which I computed with miceadds::glm.cluster.

fullmodel3 <- miceadds::glm.cluster(data = SDdataset17,
                                formula = stigmatisation_dummy_num ~ gender + age +
                                  agesquared + education_new + publicsector +
                                  retired + socialisation_sd + selfplacement_num +
                                  years_membership + voteshare,
                          cluster = "voteshare", family = "binomial")

Given that I am not using glm(), most functions I have seen around do not work.

Any suggestions?

edited Jan 12 '22 at 13:25

asked Jan 12 '22 at 13:08

Sofia Ammassari

See: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example – william3031 Jan 21 '22 at 03:44

How can I calculate marginal effects from a binomial logistic model with clustered standard errors in R studio?

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