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pchc

Calculate the Paretian Classification of Health Change


Description

Calculate the Paretian Classification of Health Change (PCHC) for two EQ-5D datasets.

Usage

pchc(
  pre,
  post,
  version = "5L",
  no.problems = TRUE,
  totals = TRUE,
  by.dimension = FALSE,
  ignore.invalid = TRUE,
  dimensions = .getDimensionNames()
)

Arguments

pre

data.frame, numeric or character. For data.frame default column names should be MO, SC, UA, PD and AD representing Mobility, Self-care, Usual activities, Pain/discomfort and Anxiety/depression. Vector using five digit format can also be used.

post

data.frame, numeric or character. For data.frame default column names should be MO, SC, UA, PD and AD representing Mobility, Self-care, Usual activities, Pain/discomfort and Anxiety/depression. Vector using five digit format can also be used.

version

string of value "3L" or "5L" to indicate instrument version.

no.problems

boolean. Summarise 11111 "No change" subjects in a "No problems" group.

totals

boolean. Include a summary total.

by.dimension

boolean. Summarise results by each EQ-5D dimension rather than by the whole dataset.

ignore.invalid

boolean whether to ignore invalid scores. TRUE returns NA, FALSE throws an error.

dimensions

character vector, specifying "dimension" column names. Defaults are "MO", "SC", "UA", "PD" and "AD".

Value

a data.frame or list of data.frames of changes according to PCHC. contain dimensions names and rows the EQ-5D score.


eq5d

Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index Scores

v0.10.0
MIT + file LICENSE
Authors
Fraser Morton [aut, cre], Jagtar Singh Nijjar [aut]
Initial release

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