missing_compare: Compare missing data

In finalfit: Quickly Create Elegant Regression Results Tables and Plots when Modelling

Compare missing data

Description

Compare missing data

Usage

missing_compare(
  .data,
  dependent,
  explanatory,
  p = TRUE,
  na_include = FALSE,
  ...
)

Arguments

.data	Dataframe.
dependent	Variable to test missingness against other variables with.
explanatory	Variables to have missingness tested against.
p	Logical: Include null hypothesis statistical test.
na_include	Include missing data in explanatory variables as a factor level.
...	Other arguments to summary_factorlist().

Value

A dataframe comparing missing data in the dependent variable across explanatory variables. Continuous data are compared with an Analysis of Variance F-test by default. Discrete data are compared with a chi-squared test.

Examples

library(finalfit)

explanatory = c("age", "age.factor", "extent.factor", "perfor.factor")
dependent = "mort_5yr"

colon_s %>%
  ff_glimpse(dependent, explanatory)

colon_s %>%
 missing_pattern(dependent, explanatory)

colon_s %>%
  missing_compare(dependent, explanatory)

finalfit documentation built on Nov. 17, 2023, 1:09 a.m.