The package permits the covariate effects of trinomial regression models to be represented graphically by means of a ternary plot. The aim of the plots is helping the interpretation of regression coefficients in terms of the effects that a change in regressors’ values has on the probability distribution of the dependent variable. Such changes may involve either a single regressor, or a group of them (composite changes), and the package permits both cases to be handled in a user-friendly way. Theoretical and methodological details are illustrated and discussed in Santi, Dickson, and Espa (2019), whereas a detailed illustration of the package and its features is available in Santi et al. (2022).
The package can read the results of both categorical and ordinal
trinomial logit regression fitted by various functions (see the next
section) and creates a field3logit
object which may be represented by
means of functions gg3logit
and stat_field3logit
.
The plot3logit
package inherits graphical classes and methods from the
package ggtern
(Hamilton and Ferry 2018) which, in turn, is based on
the package ggplot2
(Wickham 2016).
Graphical representation based on standard graphics is made
available through the package Ternary
(Smith 2017) by functions
plot3logit
and TernaryField
, and by the plot
method of
field3logit
objects.
See the help of field3logit
for representing composite effects and
multifield3logit
for drawing multiple fields and the presentation
vignette plot3logit-overview
by typing:
vignette('plot3logit-overview', package = 'plot3logit')
The paper published on Journal of Statistical Software (Santi et al. 2022) can be read as a pdf vignette by typing:
vignette('plot3logit-jss', package = 'plot3logit')
Function field3logit
of package plot3logit
can read trinomial
regression estimates from the output of the following functions:
clm
and clm2
of package ordinal
(ordinal logit regression);mlogit
of package mlogit
(logit regression);multinom
of package nnet
(logit regression);polr
of package MASS
(ordinal logit regression);vgam
and vglm
of package VGAM
(logit regression).Moreover, explicit estimates can be passed to field3logit()
. See the
help of the package (type ? 'plot3logit-package'
) and the help of
functions field3logit()
and extract3logit()
for further details.
Fit a trilogit model by means of package nnet
where the student’s
employment situation is analysed with respect to all variables in the
dataset cross_1year
:
data(cross_1year)
library(nnet)
mod0 <- multinom(employment_sit ~ ., data = cross_1year)
The gender effect is analysed by means of a ternary plot which is
generated in two steps, however, package plot3logit
should be loaded:
library(plot3logit)
Firstly, the vector field is computed:
field0 <- field3logit(mod0, 'genderFemale')
Secondly, the field is represented on a ternary plot, using either
gg
-graphics:
gg3logit(field0) + stat_field3logit()
or standard graphics:
plot(field0)
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