In Big-Life-Lab/recodeflow: Contains functions to interface with variable details sheets, including recoding variables and converting them to PMML

knitr::opts_chunk$set(echo = TRUE)
source("../R/test_data_generator.R")

Introduction

recodeflow supports the use of derived variables. Derived variables can be any custom function as long as the variable can be calculated on a per row basis. Functions requiring operations across rows or on the full data set are not supported.

The two most common uses for derived variables are:

• Variables derived from two or more variables,
• Variables that are derived using math equations (e.g., BMI is calculated by dividing weight by the square of height).

To create derived variables, you need to complete two steps:

1. Create and load a customized function.
2. Add the derived variable to the variable_details and variables worksheets.

Example of a derived function

We'll walk through an example of creating a derived variable with our example data.

Our customized derived function is multiplying the blood concentration of cholesterol (chol) with the blood concentration of bilirunbin (bili).

1. Create and load a customized function for your derived variables.

Create the custom function: Here is the customized function for our derived variable (chol*bili):

#example_der_fun caluclates chol*bili
#@param chol the row value for chol
#@param bili the row value for bili
#@export 
example_der_fun <- function(chol, bili){
  # as numeric is used to coerce in case categorical numeric variables are used.
  # Warning either chol or bili being NA will result in NA return
  example_der <- as.numeric(chol)*as.numeric(bili)

  return(example_der)
}

Note: You must use roxygen2 documentation for custom functions otherwise the function cannot be attached to a package. See roxygen2 on how to format and document your function.

Load the custom function into your R environment. Load the customized function by either:

• entering your functions into the console and running the code, or
• attaching the functions to your own package using the build and install tool. Then load your package using "library("name of package")" or by using the rec_with_table parameter to pass the path to your function R script.

If you don't load the customized function you cannot create the derived variable.

2. Add the derived variable to the variable_details and variables worksheets.

Add the derived variable to the variables worksheet. You'll use the same nomenclature as any other variable. See the article variables_sheet for nomenclature rules.

Add the derived variable to the variable_details. See the article variable_details for nomenclature rules.

3. Recode the derived variable

Use the function rec_with_table to recode your derived function.

1) Load recodeflow

#Load the package
library(recodeflow)

2) Recode the underlying variables (chol and bili) and the derived variable (example_der).

derived1 <- rec_with_table(data = tester1,
                          variables = c("chol", "bili","example_der"),
                          variable_details = variable_details,
                          log = TRUE)

Big-Life-Lab/recodeflow documentation built on Jan. 19, 2024, 10:41 p.m.