When teaching about regression it can be useful to visualize the data as a point plot with the
outcome on the y-axis and the explanatory variable on the x-axis. For regression models, this is
most easily achieved by calling ggformula::gf_lm(), with empty models
ggformula::gf_hline() using the mean, and a more complicated call to
ggformula::gf_segment() for group models. This function simplifies this
by making a guess about what kind of model you are plotting (empty/null, regression, group) and
then making the appropriate plot layer for it.
gf_model(object, model, ...)a gg object (a plot layer) that can be added to a plot.
A plot created with the ggformula package.
Additional arguments. Typically these are (a) ggplot2 aesthetics to be set with
attribute = value, (b) ggplot2 aesthetics to be mapped with attribute = ~ expression, or
(c) attributes of the layer as a whole, which are set with attribute = value.
This function only works with models that have a continuous outcome measure.