plot_or {plotor} | R Documentation |
Plot OR
Description
Produces an Odds Ratio plot to visualise the results of a logistic regression analysis.
Usage
plot_or(glm_model_results, conf_level = 0.95, confint_fast_estimate = FALSE)
Arguments
glm_model_results |
Results from a binomial Generalised Linear Model (GLM), as produced by |
conf_level |
Numeric between 0.001 and 0.999 (default = 0.95). The confidence level to use when setting the confidence interval, most commonly will be 0.95 or 0.99 but can be set otherwise. |
confint_fast_estimate |
Boolean (default = |
Value
an object of class gg
and ggplot
See Also
See vignette('using_plotor', package = 'plotor') for more details on use.
More details and examples are found on the website: https://craig-parylo.github.io/plotor/index.html
Examples
# libraries
library(plotor)
library(datasets)
library(dplyr)
library(ggplot2)
library(stats)
library(forcats)
library(tidyr)
# get some data
df <- datasets::Titanic |>
as_tibble() |>
# convert aggregated counts to individual observations
filter(n > 0) |>
uncount(weights = n) |>
# convert character variables to factors
mutate(across(where(is.character), as.factor))
# perform logistic regression using `glm`
lr <- glm(
data = df,
family = 'binomial',
formula = Survived ~ Class + Sex + Age
)
# produce the Odds Ratio plot
plot_or(lr)