plotor (version 0.7.0)

table_or: Table OR

Description

Produces a formatted table showing the outputs from the Odds Ratio analysis, including details on covariate characteristics and model results.

Usage

table_or(
  glm_model_results,
  conf_level = 0.95,
  output = "tibble",
  confint_fast_estimate = FALSE
)

Value

The returned object depends on the output parameter:

• If output = 'tibble', the function returns an object of class "tbl_df", "tbl" and "data.frame".

• If output = 'gt', the function returns an object of class "gt_tbl" and "list"

Arguments

glm_model_results

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

conf_level

Numeric value between 0.001 and 0.999 (default = 0.95) specifying the confidence level for the confidence interval.

output

String describing of the output type (default = 'tibble'). Options include 'tibble' and 'gt'.

confint_fast_estimate

Boolean (default = FALSE) indicating whether to use a faster estimate of the confidence interval. Note: this assumes normally distributed data, which may not be suitable for your data.

Details

The table includes the following information:

• Covariate characteristics:

  • Number of observations for each characteristic

  • Number of observiations resulting in the outcome of interest

  • Conversion rate of outcome by the number of observations

• Model results:

  • Estimated Odds Ratio, standard error and p-value

  • Calculated confidence interval for the specified confidence level

• A visualisation of the OR plot is also provided for an at-a-glance view of the model results

Includes details on the characteristics of the covariates, such as:

• the number of observations for each characteristic,

• the number of observations resulting in the outcome of interest,

• the conversion rate of outcome by the number of observations,

Details are calculated showing the:

• estimated Odds Ratio, standard error and p-value,

• calculated confidence interval for the confidence level,

Also included is a visualisation of the OR plot to provide an at-a-glance view of the model results.

Examples

# Load the Titanic dataset
df <- datasets::Titanic |>
  dplyr::as_tibble() |>
  # convert aggregated counts to individual observations
  dplyr::filter(n > 0) |>
  tidyr::uncount(weights = n) |>
  # convert character variables to factors
  dplyr::mutate(dplyr::across(dplyr::where(is.character), as.factor))

# Perform logistic regression using `glm`
lr <- stats::glm(
  data = df,
  family = 'binomial',
  formula = Survived ~ Class + Sex + Age
)

# Produce the Odds Ratio table as a tibble
table_or(lr)

# Produce the Odds Ratio table as a gt object
table_or(lr, output = 'gt')