contribution.svyglm <-
function(object, ranker, correction = TRUE) {
# The ranking variable (wealth, income,...) should be given explicitely.
# Throw an error if this is not a numeric one
if (class(ranker) != "numeric") stop("Not a numeric ranking variable")
# extract the outcome of the svyglm object
outcome <- predict(object, newdata = object$model[,-1], vcov = FALSE)
# extract the model matrix of the svyglm object
mm <- model.matrix(object)
# extract the weights of the svyglm object
wt <- 1 / object$survey.design$prob
# retrieve the coefficients for all variables except the intercept from the model object
betas <- coefficients(object)[-1]
# call the backend decomposition function
results <- decomposition(outcome, betas, mm, ranker, wt, correction)
return(results)
}
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