Package: eq5dsuite 2.1.0

Kim Rand

eq5dsuite: Handling and Analysing 'EQ-5D' Data

The EQ-5D is a widely-used standardised instrument for measuring Health Related Quality Of Life (HRQOL), developed by the EuroQol group <https://euroqol.org/>. It assesses five dimensions; mobility, self-care, usual activities, pain/discomfort, and anxiety/depression, using either a three-level (EQ-5D-3L) or five-level (EQ-5D-5L) scale. Scores from these dimensions are commonly converted into a single utility index using country-specific value sets, which are critical in clinical and economic evaluations of healthcare and in population health surveys. The eq5dsuite package enables users to calculate utility index values for the EQ-5D instruments, including crosswalk utilities using the original crosswalk developed by van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008> (mapping EQ-5D-5L responses to EQ-5D-3L index values), or the recently developed reverse crosswalk by van Hout et al. (2021) <doi:10.1016/j.jval.2021.03.009> (mapping EQ-5D-3L responses to EQ-5D-5L index values). Users are allowed to add and/or remove user-defined value sets. Additionally, the package provides tools to analyse EQ-5D data according to the recommended guidelines outlined in "Methods for Analyzing and Reporting EQ-5D data" by Devlin et al. (2020) <doi:10.1007/978-3-030-47622-9>.

Authors:Kim Rand [aut, cre], Oliver Rivero-Arias [aut], Iryna Schlackow [aut], Anabel Estévez-Carrillo [aut]

eq5dsuite_2.1.0.tar.gz
eq5dsuite_2.1.0.zip(r-4.7-any)eq5dsuite_2.1.0.zip(r-4.6-any)eq5dsuite_2.1.0.zip(r-4.5-any)
eq5dsuite_2.1.0.tgz(r-4.6-any)eq5dsuite_2.1.0.tgz(r-4.5-any)
eq5dsuite_2.1.0.tar.gz(r-4.7-any)eq5dsuite_2.1.0.tar.gz(r-4.6-any)
eq5dsuite_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
eq5dsuite/json (API)

# Install 'eq5dsuite' in R:
install.packages('eq5dsuite', repos = c('https://mathsinhealth.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mathsinhealth/eq5dsuite-r/issues

Datasets:

On CRAN:

Conda:

6.03 score 18 scripts 423 downloads 51 exports 20 dependencies

Last updated from:aebe991922. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK181
source / vignettesOK276
linux-releaseOK456
macos-releaseOK129
macos-oldrelOK120
windows-develOK308
windows-releaseOK113
windows-oldrelOK115
wasm-releaseOK292

Exports:eq5deq5d_profile_better_dimensions_by_group_ploteq5d_profile_change_summaryeq5d_profile_density_curveeq5d_profile_dimension_change_tableeq5d_profile_health_profile_grideq5d_profile_level_summaryeq5d_profile_level_summary_by_groupeq5d_profile_lfs_distributioneq5d_profile_lfs_mean_utilityeq5d_profile_lfs_utility_ploteq5d_profile_lfs_utility_summaryeq5d_profile_lss_utility_ploteq5d_profile_lss_utility_summaryeq5d_profile_mixed_dimensions_by_group_ploteq5d_profile_pchc_by_group_ploteq5d_profile_pchc_tableeq5d_profile_pchc_with_no_problems_tableeq5d_profile_shannoneq5d_profile_top_stateseq5d_profile_worse_dimensions_by_group_ploteq5d_utility_by_group_ploteq5d_utility_change_by_group_ploteq5d_utility_distribution_ploteq5d_utility_norms_comparisoneq5d_utility_over_time_ploteq5d_utility_summaryeq5d_utility_summary_by_groupeq5d_utility_vas_scatter_ploteq5d_vas_distribution_tableeq5d_vas_grouped_distribution_ploteq5d_vas_histogrameq5d_vas_summaryeq5d3leq5d5leq5dy3leqvs_addeqvs_displayeqvs_dropeqvs_loadeqxweqxw_UKeqxwreqxwr_UKmake_all_EQ_indexesmake_all_EQ_statesmake_dummiesrun_apptoEQ5DdimstoEQ5Dindexupdate_value_sets

Dependencies:clicpp11curlfarverggplot2gluegtableisobandlabelinglifecyclemomentsR6rappdirsRColorBrewerrlangS7scalesvctrsviridisLitewithr

Crosswalk methods
Introduction | When to use crosswalk methods | The current NICE position | Original crosswalk: eqxw() | Reverse crosswalk: eqxwr() | NICE DSU mapping, 5L to 3L: eqxw_UK() | NICE DSU mapping, 3L to 5L: eqxwr_UK() | Mapping a mean value | Crosswalk compatibility with custom value sets | References

Last update: 2026-10-05
Started: 2026-04-22

Analysing EQ-5D data
Introduction | Worked example 1: Hip replacement outcomes | Data preparation | Pre-operative profile distribution | Most common health states | Informativity: Shannon's indices | Change between time points: PCHC | Dimensions driving improvement | EQ-5D value summary | EQ VAS summary | Worked example 2: Comparing two procedures | Profile comparison by group | EQ-5D value comparison | LSS analysis by group | Further reading | References

Last update: 2026-10-02
Started: 2026-04-22

Custom value sets
Introduction | Adding a custom value set | Saving a custom value set permanently | Removing a custom value set | Validation | Using custom value sets with crosswalk methods | Keeping value sets up to date

Last update: 2026-10-02
Started: 2026-04-22

Getting started with eq5dsuite
Introduction | Installation | Available value sets | Calculating EQ-5D values | EQ-5D-3L | EQ-5D-5L | EQ-5D-Y-3L | Custom value sets | Keeping value sets up to date | Next steps

Last update: 2026-10-02
Started: 2026-04-22

Keeping value sets up to date
Introduction | How the update system works | Checking for updates | Checking specific instruments | Non-interactive updates | Automatic migrations | Value sets repository

Last update: 2026-04-22
Started: 2026-04-22

Readme and manuals

Help Manual

Help pageTopics
eq5dsuite: Standardised Tools for EQ-5D Analysiseq5dsuite-package eq5dsuite
.EQxwrprob.EQxwrprob
Helper function for frequency of levels by dimensions tables.freqtab
.pstate3t5.pstate3t5
.pstate5t3.pstate5t3
eq5deq5d
eq5d_profile_better_dimensions_by_group_plot: Percentage of Respondents Who Improved in Each EQ-5D Dimension, by Group This function calculates how many respondents improved in each dimension between two time points and summarizes the results for each group. It then produces a dimension-focused chart illustrating improvement percentages by dimension.eq5d_profile_better_dimensions_by_group_plot
eq5d_profile_change_summary: Frequency of levels by dimensions, by follow-upeq5d_profile_change_summary
eq5d_profile_density_curve: Generate a Health State Density Curve (HSDC) for EQ-5D Dataeq5d_profile_density_curve
eq5d_profile_dimension_change_table: Changes in levels in each dimension, percentages of total and of type of changeeq5d_profile_dimension_change_table
eq5d_profile_health_profile_grid: Health Profile Grid (HPG) for Two Time Pointseq5d_profile_health_profile_grid
eq5d_profile_level_summary: Frequency of levels by dimensions, cross-sectionaleq5d_profile_level_summary
eq5d_profile_level_summary_by_group: Frequency of levels by dimensions, separated by categoryeq5d_profile_level_summary_by_group
eq5d_profile_lfs_distribution: Distribution of the EQ-5D states by LFS (Level Frequency Score)eq5d_profile_lfs_distribution
eq5d_profile_lfs_mean_utility: Number of observations in the LFS (Level Frequency Score) according to the EQ-5D valueseq5d_profile_lfs_mean_utility
eq5d_profile_lfs_utility_plot: EQ-5D values plotted against LFSeq5d_profile_lfs_utility_plot
eq5d_profile_lfs_utility_summary: Summary statistics of EQ-5D values by LFS (Level Frequency Score)eq5d_profile_lfs_utility_summary
eq5d_profile_lss_utility_plot: EQ-5D values plotted against LSSeq5d_profile_lss_utility_plot
eq5d_profile_lss_utility_summary: Summary statistics for the EQ-5D values by all the different LSSs (Level Sum Scores)eq5d_profile_lss_utility_summary
eq5d_profile_mixed_dimensions_by_group_plot: Percentage of Respondents Who Had a Mixed Change Overall, by Dimension Improved or Worsened, Grouped by Procedure (or Other Grouping)eq5d_profile_mixed_dimensions_by_group_plot
eq5d_profile_pchc_by_group_plot: Paretian Classification of Health Change (PCHC) by Group This function computes PCHC categories between two time points for each subject, stratifies them by a grouping variable, and produces a single bar chart with side-by-side bars showing the distribution of PCHC categories.eq5d_profile_pchc_by_group_plot
eq5d_profile_pchc_table: Changes in health according to the PCHC (Paretian Classification of Health Change)eq5d_profile_pchc_table
eq5d_profile_pchc_with_no_problems_table: Changes in health according to the PCHC, taking account of those with no problemseq5d_profile_pchc_with_no_problems_table
eq5d_profile_shannon: Shannon's informativity indiceseq5d_profile_shannon
eq5d_profile_top_states: Prevalence of the 10 most frequently observed self-reported health stateseq5d_profile_top_states
This function identifies respondents with a "Worsen" PCHC state (i.e., overall health state got worse between levels_fu[1] and levels_fu[2]), checks dimension-specific changes (e.g., mo_diff < 0), and summarizes by a grouping variable (e.g., procedure) and time points. It returns a data table and a ggplot object.eq5d_profile_worse_dimensions_by_group_plot
eq5d_utility_by_group_plot: Mean EQ-5D values and 95% confidence intervals: all vs by groupvareq5d_utility_by_group_plot
eq5d_utility_change_by_group_plot: EQ-5D values: smoothed lines and confidence intervals by groupvareq5d_utility_change_by_group_plot
eq5d_utility_distribution_plot: EQ-5D values: smoothed lines and confidence intervals by groupvareq5d_utility_distribution_plot
eq5d_utility_norms_comparison:EQ-5D values: by age and groupvareq5d_utility_norms_comparison
eq5d_utility_over_time_plot: EQ-5D values by timepoints: mean values and 95% confidence intervalseq5d_utility_over_time_plot
eq5d_utility_summary: EQ-5D values: by timepointseq5d_utility_summary
eq5d_utility_summary_by_group:EQ-5D values: by groupvareq5d_utility_summary_by_group
eq5d_utility_vas_scatter_plot: EQ-5D values: smoothed lines and confidence intervals by groupvareq5d_utility_vas_scatter_plot
eq5d_vas_distribution_table: EQ VAS Scores frequency of mid-pointseq5d_vas_distribution_table
eq5d_vas_grouped_distribution_plot: Mid-point EQ VAS scoreseq5d_vas_grouped_distribution_plot
eq5d_vas_histogram: EQ VAS scoreseq5d_vas_histogram
eq5d_vas_summary: EQ VAS Score by timepointseq5d_vas_summary
eq5d3leq5d3l
eq5d5leq5d5l
eq5dy3leq5dy3l
eqvs_addeqvs_add
eqvs_displayeqvs_display
eqvs_dropeqvs_drop
eqvs_loadeqvs_load
eqxweqxw
eqxw_UKeqxw_UK
eqxwreqxwr
eqxwr_UKeqxwr_UK
example_dataexample_data
make_all_EQ_indexesmake_all_EQ_indexes
make_all_EQ_statesmake_all_EQ_states
EQ_dummiesmake_dummies
Launch the eq5dsuite Shiny Applicationrun_app
toEQ5DdimstoEQ5Ddims
Convert EQ-5D dimension scores to a five-digit profile indextoEQ5Dindex
Update eq5dsuite value setsupdate_value_sets