effect of a continuous variable in a logistic regression

[Jakub_Komarek]

Hi,

I created a logistic regression and one fo the explanatory variables is age in a continuous format. I wonder if I could examine the effect of this variable along the range 18 - 90. I would like to know whether there is any 'jump'. Do you have any advice?

Many thanks,

Jakub

[technocrat]

See my post using the CHD dataset, which contains the binary outcome of coronary heart disease detected against age cohort, using the continuous variable age binned into age groups.

[Max]

I suggest using a generalized additive model to plot the smooths for the predictor (similar to geom_smooth()). For example:

library(modeldata)
library(mgcv)
#> Loading required package: nlme
#> This is mgcv 1.8-33. For overview type 'help("mgcv-package")'.

data("two_class_dat")

mod <- gam(Class ~ s(A) + s(B), data = two_class_dat, family = binomial)

# The `trans` argument puts them back on the probability scale

plot(mod, trans = function(x) binomial()$linkinv(x), pages = 1)

^{Created on 2021-01-20 by the reprex package (v0.3.0)}