iqr4tab and prop4tab

2 min read notes

Below are a couple of functions I use for summarizing variables. These are useful for evaluating characteristics in different strata.

iqr4tab()

This function calculates the median and 25th, 75th quartile (IQR) and formats the output for a table:

iqr4tab <- function(x, digits = 2, na.rm = TRUE) {
  
  nums <- fivenum(x, na.rm = na.rm)[2:4]
  nums <- round(nums, digits)
  paste0(nums[2], " (", nums[1], ",", nums[3], ")")
  
}

prop4tab()

This function will calculate count and proportion for both levels of a binary variable and format for a table:

prop4tab <- function(x, level = "1", digits = 1) {
  
  x <- as.factor(x)
  n_total <- length(x)
  
  if (is.na(level) | level == "NA") {
    
    level <- "NA"
    n_level1 <- length(x[x==level])
    
  } else {
    
    n_level1 <- length(x[x==level & !is.na(x)])
    
  }

  prop <- n_level1/n_total
  paste0(n_level1, " (", round(prop*100,digits),")")

}

Example

The following example uses data from the AmesHousing package:

library(AmesHousing)
library(dplyr)
library(tidyr)

ames <- make_ames()
ames %>%
  mutate(House_Style = ifelse(House_Style == "One_Story","single story", "multi story")) %>%
  group_by(House_Style) %>%
  summarise(Price = iqr4tab(Sale_Price))
## # A tibble: 2 x 2
##   House_Style  Price                 
##   <chr>        <chr>                 
## 1 multi story  167500 (132000,213000)
## 2 single story 155000 (127000,213750)
ames %>%
  mutate(House_Style = ifelse(House_Style == "One_Story","single story", "multi story")) %>%
  group_by(House_Style) %>%
  summarise(Central_Air = prop4tab(Central_Air, level = "Y"))
## # A tibble: 2 x 2
##   House_Style  Central_Air
##   <chr>        <chr>      
## 1 multi story  1344 (92.8)
## 2 single story 1390 (93.9)
ames %>%
  mutate(House_Style = ifelse(House_Style == "One_Story", "single story", "multi story"),
         Fireplace = ifelse(Fireplaces == 0, 0, 1)) %>%
  group_by(House_Style) %>%
  summarise(Price = iqr4tab(Sale_Price),
            Rooms = iqr4tab(TotRms_AbvGrd),
            AC = prop4tab(Central_Air, level = "Y"),
            Fireplace = prop4tab(Fireplace)) %>%
  gather(variable, summary, -House_Style) %>%
  spread(House_Style, summary)
## # A tibble: 4 x 3
##   variable  `multi story`          `single story`        
##   <chr>     <chr>                  <chr>                 
## 1 AC        1344 (92.8)            1390 (93.9)           
## 2 Fireplace 801 (55.3)             707 (47.7)            
## 3 Price     167500 (132000,213000) 155000 (127000,213750)
## 4 Rooms     7 (6,8)                6 (5,7)
R

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