.summary_cts_by_fu

This function summarizes a continuous variable for each follow-up (FU) and calculates various statistics such as mean, standard deviation, median, mode, kurtosis, skewness, minimum, maximum, range, and number of observations. It also reports the total sample size and the number (and proportion) of missing values for each FU. 
The input `df` must contain an ordered FU variable and the continuous variable of interest. 
The name of the continuous variable must be specified using `name_v`. 
The wrapper is used in Table 3.1 (for VAS) or Table 4.2 (for EQ-5D utility)

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

Manipulating and Analysing EQ-5d Data

Iryna Schlackow

Anabel Estévez-Carrillo

.summary_cts_by_fu function

<dl><dt>df</dt>
<dd>A data frame containing the FU and continuous variable of interest. The dataset must contain an ordered `fu` variable.</dd>
<dt>name_v</dt>
<dd>A character string with the name of the continuous variable in `df` to be summarised.</dd></dl>

Arguments

Wrapper to summarise a continuous variable by follow-up (FU) — .summary_cts_by_fu

<dl>

<dt>df</dt>
<dd>A data frame containing the FU and continuous variable of interest. The dataset must contain an ordered `fu` variable.</dd>


<dt>name_v</dt>
<dd>A character string with the name of the continuous variable in `df` to be summarised.</dd>

</dl>

.summary_cts_by_fu: Wrapper to summarise a continuous variable by follow-up (FU)

Description

Usage

Value

Arguments

Examples