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Simulated EQ‑5D‑5L Health Status Dataset

Source: R/data.R
raw_eq5d5l.Rd

`raw_eq5d5l` contains a fully synthetic version of the EQ‑5D‑5L instrument for two simulated participants (`P01` and `P02`) across three study stages: "Registration", "Day-7", and "Day-14". The dataset includes ISO‑8601 timestamped assessments and categorical responses for each of the five EQ‑5D‑5L dimensions.

Usage

raw_eq5d5l

Format

A tibble with the following variables:

userid

Character participant ID ("P01", "P02").

stage

Assessment stage ("Registration", "Day-7", "Day-14").

localTimestamp

Character ISO‑8601 timestamp including milliseconds and timezone.

SC

Self‑Care domain level ("SC1"–"SC5").

AD

Anxiety/Depression domain level ("AD1"–"AD5").

UA

Usual Activities domain level ("UA1"–"UA5").

MB

Mobility domain level ("MB1"–"MB5").

PD

Pain/Discomfort domain level ("PD1"–"PD5").

Details

This dataset is simulated and intended for demonstrating workflows and examples within the `hypometrics` package.

Participants and timing

  • "P01" — Registration time: "2026-01-01 07:17:00" (UTC)

  • "P02" — Registration time: "2026-01-02 15:52:00" (UTC)

Follow‑up assessments occur exactly **7** and **14** days after Registration for each participant.

EQ‑5D‑5L dimensions (each with 5 levels)

Each EQ‑5D‑5L domain is represented using the 5‑level structure, encoded as:

  • SC1–SC5: **Self‑Care**

  • AD1–AD5: **Anxiety/Depression**

  • UA1–UA5: **Usual Activities**

  • MB1–MB5: **Mobility**

  • PD1–PD5: **Pain / Discomfort**

Generation script

This dataset is produced reproducibly using:


data-raw/simulate_raw_eq5d5l.R

Examples

data(raw_eq5d5l, package = "hypometrics")

# Inspect structure
dplyr::glimpse(raw_eq5d5l)
#> Rows: 6
#> Columns: 8
#> $ userid         <chr> "P01", "P01", "P01", "P02", "P02", "P02"
#> $ stage          <chr> "Day-14", "Day-7", "Registration", "Day-14", "Day-7", "…
#> $ localTimestamp <chr> "2026-01-15T07:17:00.000+00:00", "2026-01-08T07:17:00.0…
#> $ SC             <chr> "SC5", "SC3", "SC1", "SC1", "SC4", "SC5"
#> $ AD             <chr> "AD2", "AD2", "AD1", "AD2", "AD3", "AD5"
#> $ UA             <chr> "UA3", "UA3", "UA2", "UA4", "UA4", "UA2"
#> $ MB             <chr> "MB4", "MB5", "MB3", "MB2", "MB4", "MB5"
#> $ PD             <chr> "PD1", "PD2", "PD4", "PD3", "PD2", "PD1"

# Show values for P01
raw_eq5d5l %>% dplyr::filter(userid == "P01")
#> # A tibble: 3 × 8
#>   userid stage        localTimestamp               SC    AD    UA    MB    PD   
#>   <chr>  <chr>        <chr>                        <chr> <chr> <chr> <chr> <chr>
#> 1 P01    Day-14       2026-01-15T07:17:00.000+00:… SC5   AD2   UA3   MB4   PD1  
#> 2 P01    Day-7        2026-01-08T07:17:00.000+00:… SC3   AD2   UA3   MB5   PD2  
#> 3 P01    Registration 2026-01-01T07:17:00.000+00:… SC1   AD1   UA2   MB3   PD4  

# Summarise EQ-5D-5L domains by participant and stage
raw_eq5d5l %>%
  dplyr::group_by(userid, stage) %>%
  dplyr::summarise(
    across(c(SC, AD, UA, MB, PD), ~ dplyr::n_distinct(.x)),
    .groups = "drop"
  )
#> # A tibble: 6 × 7
#>   userid stage           SC    AD    UA    MB    PD
#>   <chr>  <chr>        <int> <int> <int> <int> <int>
#> 1 P01    Day-14           1     1     1     1     1
#> 2 P01    Day-7            1     1     1     1     1
#> 3 P01    Registration     1     1     1     1     1
#> 4 P02    Day-14           1     1     1     1     1
#> 5 P02    Day-7            1     1     1     1     1
#> 6 P02    Registration     1     1     1     1     1