example_data

A dataset containing patient-level data in a long format.

datasets

The EQ-5D is a widely-used standarized 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 analyze 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>.

Kim Rand

eq5dsuite

Handling and Analysing EQ-5d Data

Iryna Schlackow

Anabel Estévez-Carrillo

example_data function

A data frame with 10000 rows and 14 variables:<dl>
 <dt><code>id</code></dt>
<dd>double Patient id</dd> <dt><code>time</code></dt>
<dd>character Follow-up (Pre-op / Post-op)</dd> <dt><code>mo</code></dt>
<dd>double EQ-5D-5L Mobility dimension</dd> <dt><code>sc</code></dt>
<dd>double EQ-5D-5L Self-care dimension</dd> <dt><code>ua</code></dt>
<dd>double EQ-5D-5L Usual activities dimension</dd> <dt><code>pd</code></dt>
<dd>double EQ-5D-5L Pain / discomfort dimension</dd> <dt><code>ad</code></dt>
<dd>double EQ-5D-5L Anxiety/depression dimension</dd> <dt><code>vas</code></dt>
<dd>double Value of the VAS scale measurememnt</dd> <dt><code>providercode</code></dt>
<dd>character Provider code</dd> <dt><code>procedure</code></dt>
<dd>character Type of surgery</dd> <dt><code>year</code></dt>
<dd>character Year of intervention</dd> <dt><code>ageband</code></dt>
<dd>character Age in pre-defined ranges</dd>
 
 <dt><code>gender</code></dt>
<dd>character Patient's gender (Female / Male)</dd>
</dl>

Format

example_data — example_data

A data frame with 10000 rows and 14 variables:<dl>
 <dt><code>id</code></dt>
<dd>double Patient id</dd>

 <dt><code>time</code></dt>
<dd>character Follow-up (Pre-op / Post-op)</dd>

 <dt><code>mo</code></dt>
<dd>double EQ-5D-5L Mobility dimension</dd>

 <dt><code>sc</code></dt>
<dd>double EQ-5D-5L Self-care dimension</dd>

 <dt><code>ua</code></dt>
<dd>double EQ-5D-5L Usual activities dimension</dd>

 <dt><code>pd</code></dt>
<dd>double EQ-5D-5L Pain / discomfort dimension</dd>

 <dt><code>ad</code></dt>
<dd>double EQ-5D-5L Anxiety/depression dimension</dd>

 <dt><code>vas</code></dt>
<dd>double Value of the VAS scale measurememnt</dd>

 <dt><code>providercode</code></dt>
<dd>character Provider code</dd>

 <dt><code>procedure</code></dt>
<dd>character Type of surgery</dd>

 <dt><code>year</code></dt>
<dd>character Year of intervention</dd>

 <dt><code>ageband</code></dt>
<dd>character Age in pre-defined ranges</dd>
 
 <dt><code>gender</code></dt>
<dd>character Patient's gender (Female / Male)</dd>


</dl>

example_data: example_data

Description

Usage

Arguments

Format