.EQxwrprob              .EQxwrprob
.add_utility            Add utility values to a data frame
.check_uniqueness       Check the uniqueness of groups This function
                        takes a data frame 'df' and a vector of columns
                        'group_by', and checks whether the combinations
                        of values in the columns specified by
                        'group_by' are unique. If the combinations are
                        not unique, a warning message is printed.
.freqtab                Helper function for frequency of levels by
                        dimensions tables
.gen_colours            Generate colours for PCHC figures
.get_lfs                Calculate the Level Frequency Score (LFS)
.get_names              Replace NULL names with default values
.getmode                Get the mode of a vector.
.modify_ggplot_theme    Modify ggplot2 theme
.pchc                   Wrapper to determine Paretian Classification of
                        Health Change
.pchc_plot_by_dim       Wrapper to generate Paretian Classification of
                        Health Change plot by dimension
.pchctab                .pchctab: Changes in health according to the
                        PCHC (Paretian Classification of Health Change)
.prep_eq5d              Data checking/preparation: EQ-5D variables
.prep_fu                Data checking/preparation: follow-up variable
.prep_vas               Data checking/preparation: VAS variable
.pstate3t5              .pstate3t5
.pstate5t3              .pstate5t3
.summary_cts_by_fu      Wrapper to summarise a continuous variable by
                        follow-up (FU)
.summary_mean_ci        Wrapper to calculate summary mean with 95%
                        confidence interval
.summary_table_2_1      Wrapper for the repetitive code in
                        function_table_2_1. Data frame summary
.summary_table_4_3      Summary wrapper for Table 4.3
.summary_table_4_4      Summary wrapper for Table 4.4
eq5d                    eq5d
eq5d3l                  eq5d3l
eq5d5l                  eq5d5l
eq5dy3l                 eq5dy3l
eqvs_add                eqvs_add
eqvs_display            eqvs_display
eqvs_drop               eqvs_drop
eqvs_load               eqvs_load
eqxw                    eqxw
eqxw_UK                 eqxw_UK
eqxwr                   eqxwr
example_data            example_data
figure_1_2_1            Figure 1.2.1: Paretian Classification of Health
                        Change (PCHC) by Group This function computes
                        PCHC categories between two time points for
                        each subject, stratifies them by a grouping
                        variable, and produces a single bar chart with
                        side-by-side bars showing the distribution of
                        PCHC categories.
figure_1_2_2            Figure 1.2.2: Percentage of Respondents Who
                        Improved in Each EQ-5D Dimension, by Group This
                        function calculates how many respondents
                        improved in each dimension between two time
                        points and summarizes the results for each
                        group. The, it prodcuces a dimension-focused
                        chart illustrating improvement percentages by
                        dimension.
figure_1_2_3            This function identifies respondents with a
                        "Worsen" PCHC state (i.e., overall health state
                        got worse between levels_fu[1] and
                        levels_fu[2]), checks dimension-specific
                        changes (e.g., mo_diff < 0), and summarizes by
                        a grouping variable (e.g., procedure) and time
                        points. It returns a data table and a ggplot
                        object.
figure_1_2_4            Figure 1.2.4: Percentage of Respondents Who Had
                        a Mixed Change Overall, by Dimension Improved
                        or Worsened, Grouped by Procedure (or Other
                        Grouping)
figure_1_2_5            Figure 1.2.5: Health Profile Grid (HPG) for Two
                        Time Points
figure_1_3_1            Figure 1.3.1: EQ-5D values plotted against LSS
figure_1_3_2            Figure 1.3.2: EQ-5D values plotted against LFS
figure_1_4_1            Figure 1.4.1: Generate a Health State Density
                        Curve (HSDC) for EQ-5D Data
figure_2_1              Figure 2.1: EQ VAS scores
figure_2_2              Figure 2.2: Mid-point EQ VAS scores
figure_3_1              Figure 3.1: EQ-5D values by timepoints: mean
                        values and 95% confidence intervals
figure_3_2              Figure 3.2: Mean EQ-5D values and 95%
                        confidence intervals: all vs by groupvar
figure_3_3              Figure 3.3: EQ-5D values: smoothed lines and
                        confidence intervals by groupvar
figure_3_4              Figure 3.4: EQ-5D values: smoothed lines and
                        confidence intervals by groupvar
figure_3_5              Figure 3.5: EQ-5D values: smoothed lines and
                        confidence intervals by groupvar
make_all_EQ_indexes     make_all_EQ_indexes
make_all_EQ_states      make_all_EQ_states
make_dummies            EQ_dummies
run_app                 Launch the eq5dsuite Shiny Application
table_1_1_1             Table 1.1.1: Frequency of levels by dimensions,
                        cross-sectional
table_1_1_2             Table 1.1.2: Frequency of levels by dimensions,
                        separated by category
table_1_1_3             Table 1.1.3: Prevalence of the 10 most
                        frequently observed self-reported health states
table_1_2_1             Table 1.2.1: Frequency of levels by dimensions,
                        by follow-up
table_1_2_2             Table 1.2.2: Changes in health according to the
                        PCHC (Paretian Classification of Health Change)
table_1_2_3             Table 1.2.3: Changes in health according to the
                        PCHC, taking account of those with no problems
table_1_2_4             Table 1.2.4: Changes in levels in each
                        dimension, percentages of total and of type of
                        change
table_1_3_1             Table 1.3.1: Summary statistics for the EQ-5D
                        values by all the different LSSs (Level Sum
                        Scores)
table_1_3_2             Table 1.3.2: Distribution of the EQ-5D states
                        by LFS (Level Frequency Score)
table_1_3_3             Table 1.3.3: Number of observations in the LFS
                        (Level Frequency Score) according to the EQ-5D
                        values
table_1_3_4             Table 1.3.4: Summary statistics of EQ-5D values
                        by LFS (Level Frequency Score)
table_2_1               Table 2.1: EQ VAS Score by timepoints
table_2_2               Table 2.2: EQ VAS Scores frequency of
                        mid-points
table_3_1               Table 3.1: EQ-5D values: by timepoints
table_3_2               Table 3.2 EQ-5D values: by groupvar
table_3_3               Table 3.3 EQ-5D values: by age and groupvar
toEQ5Ddims              toEQ5Ddims
toEQ5Dindex             Convert EQ-5D dimension scores to a five-digit
                        profile index
