# binomial_glm_plot

From model4you v0.9-5
by Heidi Seibold

##### 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.

##### 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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