dot-pchc function

Wrapper to determine Paretian Classification of Health Change

This internal function determines Paretian Classification of Health Change (PCHC) for each combination of the variables specified in the group_by argument. It is used in the code for table_2_4-table_2_5 and figure_2_1-figure_2_4. An EQ-5D health state is deemed to be better than another if it is better on at least one dimension and is no worse on any other dimension. An EQ-5D health state is deemed to be worse than another if it is worse in at least one dimension and is no better in any other dimension.

.pchc(df, level_fu_1, add_noprobs = FALSE)

Arguments

• df: A data frame with EQ-5D states and follow-up variable. The dataset is assumed to be have been ordered correctly.
• level_fu_1: Value of the first (i.e. earliest) follow-up. Would normally be defined as levels_fu[1].
• add_noprobs: Logical value indicating whether to include a separate classification for those without problems (default is FALSE)

Returns

A data frame with PCHC value for each combination of the grouping variables. If 'add_noprobs' is TRUE, a separate classification for those without problems is also included.

Examples

df <- data.frame(id = c(1, 1, 2, 2),
                 fu = c(1, 2, 1, 2),
                 mo = c(1, 1, 1, 1),
                 sc = c(1, 1, 5, 1),
                 ua = c(1, 1, 4, 3),
                 pd = c(1, 1, 1, 3),
                 ad = c(1, 1, 1, 1))
.pchc(df, level_fu_1 = 1, add_noprobs = TRUE)