Is there an easy way to combine two glm models in R?

I have two logistic regression models in R made with glm(). They both use the same variables, but were made using different subsets of a matrix. Is there an easy way to get an average model which gives the means of the coefficients and then use this with the predict() function?

[ sorry if this type of question should be posted on a programming site let me know and I’ll post it there ]



Do you want to take the average of the predicted probabilities, or the average of the coefficients? They will give different results, because a logistic regression involves a nonlinear transform of the linear predictor.

A function to do either would be something like this. Set avg to "prob" to get the former, or something else for the latter.

pred_comb <- function(mod1, mod2, dat, avg="prob", ...)
    xb1 <- predict(mod1, dat, type="link", ...)
    xb2 <- predict(mod2, dat, type="link", ...)
    if(avg == "prob")
        (plogis(xb1) + plogis(xb2))/2
    else plogis((xb1 + xb2)/2)

Source : Link , Question Author : Andrew , Answer Author : Hong Ooi

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