binomial_glm_plot

0th

Percentile

Plot for a given logistic regression model (glm with binomial family) with one binary covariate.

Can be used on its own but is also useable as plotfun in node_pmterminal.

Usage
binomial_glm_plot(mod, data = NULL, plot_data = FALSE,
  theme = theme_classic(), ...)
Arguments
mod

A model of class glm with binomial family.

data

optional data frame. If NULL the data stored in mod is used.

plot_data

should the data in form of a mosaic type plot be plotted?

theme

A ggplot2 theme.

...

ignored at the moment.

Aliases
  • binomial_glm_plot
Examples
# NOT RUN {
set.seed(2017)

# number of observations
n <- 1000

# balanced binary treatment
# trt <- factor(rep(c("C", "A"), each = n/2),
#               levels = c("C", "A"))

# unbalanced binary treatment
trt <- factor(c(rep("C", n/4), rep("A", 3*n/4)),
              levels = c("C", "A"))

# some continuous variables
x1 <- rnorm(n)
x2 <- rnorm(n)

# linear predictor
lp <- -0.5 + 0.5*I(trt == "A") + 1*I(trt == "A")*I(x1 > 0)

# compute probability with inverse logit function
invlogit <- function(x) 1/(1 + exp(-x))
pr <- invlogit(lp)

# bernoulli response variable
y <- rbinom(n, 1, pr)
dat <- data.frame(y, trt, x1, x2)

# logistic regression model
mod <- glm(y ~ trt, data = dat, family = "binomial")
binomial_glm_plot(mod, plot_data = TRUE)

# logistic regression model tree
ltr <- pmtree(mod)
plot(ltr, terminal_panel = node_pmterminal(ltr,
                                           plotfun = binomial_glm_plot,
                                           confint = TRUE,
                                           plot_data = TRUE))

# }
Documentation reproduced from package model4you, version 0.9-5, License: GPL-2 | GPL-3

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