plot.orm {ormPlot} | R Documentation |
Plot the prediction with confidence intervals
Description
This function plots the model predictions given that all variables that are
not included in the plot are kept constant. Hence it requires at least one
variable to produce a plot.
returns a ggplot
object that can be further customized like any
other ggplot
Usage
## S3 method for class 'orm'
plot(
x,
xval,
plot_cols = c(),
plot_rows = c(),
label_with_colname = TRUE,
facet_labels = NULL,
xlab = NULL,
ylab = NULL,
np = 100,
fun = stats::plogis,
boot.type = "bca",
conf.int = 0.95,
...
)
Arguments
x |
an object created by |
xval |
The model value plotted on the x axis |
plot_cols |
A vector of strings with other model components that should be plotted. These are put on columns. |
plot_rows |
A vector of strings with other model components that should be plotted. These are put on rows. |
label_with_colname |
Should he variable name also be included on plot row and column names |
facet_labels |
A named list of new names for variables on rows and columns |
xlab |
A custom x-axis value (if specified) |
ylab |
A custom y-axis value (if specified) |
np |
the number of equally-spaced points computed for continuous
predictors that vary, i.e., when the specified value is |
fun |
an optional transformation of the linear predictor.
Specify |
boot.type |
set to |
conf.int |
confidence level (highest posterior density interval probability for
Bayesian models). Default is 0.95. Specify |
... |
additional parameters that will be passed to |
Value
a ggplot
plot object
See Also
Examples
#load the libraries
library(rms)
library(ormPlot)
#make the datadist
dd<-datadist(educ_data)
options(datadist='dd')
#create the model
cran_model <- orm(educ_3 ~ Rural + sex + max_SEP_3 + cran_rzs, data = educ_data)
#plot the predictions of the model for varying one variable only
plot(cran_model, cran_rzs)
#customize the plotting varying all variables
plot(cran_model, cran_rzs,
plot_cols = max_SEP_3,
plot_rows = c(Rural, sex),
#setting new x-label (optional)
xlab = "Cranial volume (residuals to age an birth date)",
#setting new facet labels (optional)
facet_labels = list(Rural = c("Urban", "Rural"),
sex = c("Boys","Girls"))
)