summaryfactorlist: Summarize a set of factors (or continuous variables) by a...
In ewenharrison/summarizer: Summarizer

A function that takes a single dependent variable with a vector of explanatory variable names (continuous or categorical variables) to produce a summary table.

1
2
3

summary.factorlist(df, dependent, explanatory, cont=c("mean","median"),
	p=FALSE, na.include=FALSE, column=FALSE, total_col=FALSE,
	orderbytotal=FALSE, glm.id=FALSE, na.to.missing = TRUE)

`df`	Dataframe
`dependent`	Character vector of length 1: name of depdendent variable (2 to 5 factor levels)
`explanatory`	Character vector of any length: name(s) of explanatory variables
`cont`	Summary for continuous variables: mean (standard deviation) or median (interquartile range)
`p`	Logical: Include statistical test (see `library(Hmisc)`)
`na.include`	Logical: include missing data in summary (`NA`)
`column`	Logical: Compute margins by column rather than row
`total_col`	Logical: include a total column summing across factor levels
`orderbytotal`	Logical: order final table by total column high to low
`glm.id`	Logical: not used directly, allows merging via `summary.merge`
`na.to.missing`	Logical: convert `NA` to 'Missing' when `na.include=TRUE`

# summary.factorlist() wraps `Hmisc::summary.formula` to summarise any number of variables by a single categorical
# variable. This is usually "Table 1" of a study report.

library(summarizer)
library(tidyverse)

# Load example dataset, modified version of survival::colon
data(colon_s)

# Table 1 - Patient demographics ----
explanatory = c("age", "age.factor", "sex.factor", "obstruct.factor")
dependent = "perfor.factor"
colon_s %>%
  summary.factorlist(dependent, explanatory, p=T)

# summary.factorlist() is also commonly used to summarise any number of variables by an outcome variable (say dead yes/no).

# Table 2 - 5 yr mortality ----
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = 'mort_5yr'
colon_s %>%
  summary.factorlist(dependent, explanatory)