Plot OR

Produces an Odds Ratio plot to visualise the results of a logistic regression analysis.

Usage

plot_or(glm_model_results)

Arguments

glm_model_results

Results from a binomial Generalised Linear Model (GLM), as produced by stats::glm().

Value

plotor returns 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)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
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)
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 3 rows containing missing values or values outside the scale range
#> (`geom_errorbarh()`).
#> Warning: Removed 5 rows containing missing values or values outside the scale range
#> (`geom_point()`).