severity_ribbon_plot {valueSetCompare}

severity_ribbon_plot

Description

This function generates a ribbon plot for given utility columns, based on weighted statistics.

Usage

severity_ribbon_plot(
  df,
  utility_columns,
  weight_column = "VAS",
  weight_range = c(0:100),
  weight_values = NULL,
  weight_function = .makeWeightsMixed,
  sample_size = 1000,
  number_of_samples = 1000,
  probability_levels = c(min = 0, `2.5%` = 0.025, `25%` = 0.25, median = 0.5, `75%` =
    0.75, `97.5%` = 0.975, max = 1),
  graph_title = "",
  x_axis_title = "",
  y_axis_title = "",
  legend_name = "Type",
  legend_labels = NULL,
  y_axis_limits = c(0.15, 0.95),
  y_min_value = "2.5%",
  y_max_value = "97.5%",
  alpha_1 = 0.15,
  alpha_2 = 0.05,
  linetype_1 = 1,
  linetype_2 = 2,
  interpretation_quartiles = c(0, 0.25, 0.5, 0.75, 1),
  elevation_threshold = 0.05,
  slope_threshold = 0.02,
  color_palette = NULL,
  weighted_statistics = NULL
)

Arguments

df

A data frame containing the utility and weight columns.

utility_columns

A character vector specifying the utility columns for which the ribbon plot will be generated.

weight_column

A string specifying the column that contains the weights. Default is "VAS".

weight_range

A numeric vector specifying the range of weights. Default is c(0:100).

weight_values

A numeric vector specifying the weight values to be used. Default is NULL, in which case the weight_range will be used.

weight_function

A function to generate weights. Default is .makeWeightsMixed.

sample_size

An integer specifying the sample size for bootstrapping. Default is 1000.

number_of_samples

An integer specifying the number of bootstrap samples. Default is 1000.

probability_levels

A named vector specifying the probability levels for quantile.

graph_title

A string specifying the title of the graph. Default is an empty string.

x_axis_title

A string specifying the title for the x-axis. Default is an empty string.

y_axis_title

A string specifying the title for the y-axis. Default is an empty string.

legend_name

A string specifying the name for the legend. Default is "Type".

legend_labels

A character vector specifying the labels for the legend. Default is NULL.

y_axis_limits

A numeric vector specifying the limits for the y-axis. Default is c(0.15, 0.95).

y_min_value

A string specifying the minimum value for the y-axis.

y_max_value

A string specifying the maximum value for the y-axis.

alpha_1

A numeric value between 0 and 1 to define the transparency of the interquartile range. Default is 0.15.

alpha_2

A numeric value between 0 and 1 to define the transparency of the confidence interval range. Default is 0.05.

linetype_1

A numeric value between 0 and 1 to define the line type of the interquartile range. Default is 1 "solid".

linetype_2

A numeric value between 0 and 1 to define the line type of the confidence interval range. Default 2 "dashed".

interpretation_quartiles

A numeric vector of values between 0 and 1 to define the quantile ranges for the figure interpretation. Default is c(0, 0.25, 0.5, 0.75, 1)

elevation_threshold

A numeric value specifying the threshold for elevation differences. Default is 0.05.

slope_threshold

A numeric value specifying the threshold for slope differences. Default is 0.02.

color_palette

A character vector specifying the color palette for the plot. Default is c("#8dd3c7", "#bebada", "#80b1d3", "#fb8072", "#ffff67", "#fdb462", "#b3de69", "#fccde5", "#d9d9d9", "#bc80bd").

weighted_statistics

An optional data frame of pre-computed weighted statistics. Default is NULL.

Value

A list containing three elements: 'df' which is a data frame of weighted statistics, 'plot' which is the ggplot object representing the ribbon plot and 'interpretation' with the automatic interpretation of the ribbon plot.

Examples

  # Define dimension names for EQ-5D-3L and EQ-5D-5L
  dim.names.3L <- c("mobility", "selfcare", "activity", "pain", "anxiety")
  dim.names.5L <- c("mobility5L", "selfcare5L", "activity5L", "pain5L", "anxiety5L")
  # Compute EQ-5D scores using the eq5dsuite package
  cdta$EQ5D3L <- eq5dsuite::eq5d3l(x = cdta,
                                   country = "US", 
                                   dim.names = dim.names.3L)
  cdta$EQ5D5L <- eq5dsuite::eq5d5l(x = cdta, 
                                   country = "US", 
                                   dim.names = dim.names.5L)
  cdta$EQXW <- eq5dsuite::eqxw(x = cdta, 
                               country = "US", 
                               dim.names = dim.names.5L)
  # Get severity ribbon plot
  result <- severity_ribbon_plot(df = cdta, utility_columns = c("EQ5D3L", "EQ5D5L", "EQXW"))