plot_jointMarginalAPCeffects {APCtools}  R Documentation 
Joint plot to compare the marginal APC effects of multiple models
Description
This function creates a joint plot of the marginal APC effects of multiple estimated models. It creates a plot with one pane per age, period and cohort effect, each containing one lines for each estimated model.
Usage
plot_jointMarginalAPCeffects(
model_list,
dat,
vlines_list = NULL,
ylab = NULL,
ylim = NULL
)
Arguments
model_list 
A list of regression models estimated with

dat 
Dataset with columns 
vlines_list 
Optional list that can be used to highlight the borders of
specific age groups, time intervals or cohorts. Each element must be a
numeric vector of values on the xaxis where vertical lines should be drawn.
The list can maximally have three elements and must have names out of

ylab , ylim 
Optional ggplot2 styling arguments. 
Details
If the model was estimated with a log or logit link, the function automatically performs an exponential transformation of the effect.
Since the plot output created by the function is no ggplot2
object,
but an object created with ggpubr::ggarrange
, the overall theme
of the plot cannot be changed by adding the theme in the form of
'plot_jointMarginalAPCeffects(...) + theme_minimal(...)
'.
Instead, you can call theme_set(theme_minimal(...))
as an individual
call before calling plot_jointMarginalAPCeffects(...)
. The latter
function will then use this global plotting theme.
Value
Plot grid created with ggarrange
.
Author(s)
Alexander Bauer alexander.bauer@stat.unimuenchen.de, Maximilian Weigert maximilian.weigert@stat.unimuenchen.de
Examples
library(APCtools)
library(mgcv)
data(travel)
# plot marginal effects of one model
model_pure < gam(mainTrip_distance ~ te(age, period), data = travel)
plot_jointMarginalAPCeffects(model_pure, dat = travel)
# plot marginal effects of multiple models
model_cov < gam(mainTrip_distance ~ te(age, period) + s(household_income),
data = travel)
model_list < list("pure model" = model_pure,
"covariate model" = model_cov)
plot_jointMarginalAPCeffects(model_list, dat = travel)
# mark specific cohorts
plot_jointMarginalAPCeffects(model_list, dat = travel,
vlines_list = list("cohort" = c(1966.5,1982.5,1994.5)))