Getting started with eq5dsuite"

In eq5dsuite: Handling and Analysing EQ-5d Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment  = "#>"
)
library(eq5dsuite)

Introduction

The eq5dsuite package provides standardised tools for calculating EQ-5D preference-based values and analysing EQ-5D data following the recommendations of Devlin et al. (2020). This vignette introduces the core workflow: loading the package, exploring available value sets, and calculating EQ-5D values from profile data.

Installation

Install the released version from CRAN:

install.packages("eq5dsuite")

Install the development version from GitHub:

remotes::install_github("MathsInHealth/eq5dsuite-r")

Available value sets

The package includes country-specific value sets for the EQ-5D-3L, EQ-5D-5L, and EQ-5D-Y-3L instruments. Use eqvs_display() to see all available sets:

# List all available EQ-5D-3L value sets
eqvs_display(version = "3L")

Calculating EQ-5D values

EQ-5D-3L

The most common workflow uses a data frame with one column per EQ-5D dimension. The dim.names argument maps your column names to the five dimensions in the standard order (mobility, self-care, usual activities, pain/discomfort, anxiety/depression):

# Example data with EQ-5D-3L responses
eq5d3l_data <- data.frame(
  id = 1:5,
  mo = c(1, 2, 1, 3, 2),
  sc = c(1, 1, 2, 2, 1),
  ua = c(1, 2, 1, 3, 2),
  pd = c(2, 2, 1, 3, 3),
  ad = c(1, 1, 2, 2, 1)
)

# Calculate EQ-5D-3L values using the UK value set
eq5d3l_data$value <- eq5d3l(
  eq5d3l_data,
  country   = "UK",
  dim.names = c("mo", "sc", "ua", "pd", "ad")
)

eq5d3l_data

EQ-5D-5L

eq5d5l_data <- data.frame(
  id = 1:5,
  mo = c(1, 2, 3, 1, 2),
  sc = c(1, 1, 2, 1, 3),
  ua = c(2, 1, 3, 1, 2),
  pd = c(2, 3, 2, 1, 4),
  ad = c(1, 2, 1, 3, 2)
)

eq5d5l_data$value <- eq5d5l(
  eq5d5l_data,
  country   = "IT",
  dim.names = c("mo", "sc", "ua", "pd", "ad")
)

eq5d5l_data

EQ-5D-Y-3L

eq5dy3l_data <- data.frame(
  id = 1:5,
  mo = c(1, 2, 1, 2, 3),
  sc = c(1, 1, 2, 1, 2),
  ua = c(2, 1, 1, 3, 2),
  pd = c(1, 2, 3, 2, 1),
  ad = c(2, 1, 2, 1, 3)
)

eq5dy3l_data$value <- eq5dy3l(
  eq5dy3l_data,
  country   = "SI",
  dim.names = c("mo", "sc", "ua", "pd", "ad")
)

eq5dy3l_data

Custom value sets

If a value set is not yet included in the package, you can add your own using eqvs_add():

# Create a custom value set data frame
custom_vs <- data.frame(
  state = make_all_EQ_indexes(version = "3L"),
  MY_VS = runif(243)
)

# Register it temporarily for this session
eqvs_add(
  custom_vs,
  version     = "3L",
  country     = "My Country",
  countryCode = "MC",
  VSCode      = "MC",
  description = "Custom value set for demonstration",
  saveOption  = 1
)

# Use the custom value set
eq5d3l(c(11111, 12321), country = "MC")

Keeping value sets up to date

New EQ-5D value sets are published regularly. Use update_value_sets() to check for and install new value sets from the online repository:

update_value_sets()

Next steps

• vignette("analysing-eq5d-data") — complete analytical workflow using NHS PROMs data
• vignette("crosswalk-methods") — when and how to use crosswalk methods
• vignette("custom-value-sets") — adding and managing custom value sets
• ?eq5dsuite — full package documentation

eq5dsuite documentation built on May 14, 2026, 5:07 p.m.