MHQoL (version 0.14.0)

mhqol_utilities: Provides the scores of the MHQoL based on the textual input (as described in the manual)

Description

This function provides the utilities of the MHQoL based on textual, as described in the manual, or numeric input of the MHQoL.

Usage

mhqol_utilities(
  dimensions,
  country = "Netherlands",
  ignore_invalid = FALSE,
  ignore_NA = TRUE,
  retain_old_variables = TRUE)

Value

A dataframe containing the new utilities based on the MHQoL manual.

Arguments

dimensions

A dataframe, character vector, numeric vector, or list containing the character or numeric dimensions of the MHQoL. Must contain the following dimensions: SI (Self-Image), IN (INdependence), MO (MOod), RE (RElationships), DA (Daily Activities), PH (Physical Health), FU (FUture).

country

The country for which the utilities should be calculated. For now the only option is "Netherlands".

ignore_invalid

If TRUE, the function will ignore missing dimensions and continue processing. If FALSE, the function will stop and throw an error.

ignore_NA

If TRUE, the function will ignore NA values in the input data. If FALSE, the function will stop and throw an error.

retain_old_variables

If TRUE, the function will return the original dimensions along with the new utilities. If FALSE, the function will only return the new utilities.

Examples

# Example usage of the mhqol_utilities function

# Get the MHQoL utilities based on a character vector and do not retain old values
mhqol_utilities(
  dimensions = c(
    SI = "I think very positively about myself",
    IN = "I am very satisfied with my level of independence",
    MO = "I do not feel anxious, gloomy, or depressed",
    RE = "I am very satisfied with my relationships",
    DA = "I am very satisfied with my daily activities",
    PH = "I have no physical health problems",
    FU = "I am very optimistic about my future"
   ),
   retain_old_variables = FALSE
)

# Get the MHQoL utilities based on a numeric vector and ignore missing dimensions
mhqol_utilities(
  dimensions = c(IN = 2, MO = 1, RE = 0, DA = 3, PH = 2, FU = 1),
  ignore_invalid = TRUE
)