compute_prop_surp: Proportion of Subjects Surpassing the Threshold

In CJangelo/COA34: Psychometric Analyses Aligned with FDA COA Guidances 3 and 4

Proportion of Subjects Surpassing the Threshold

Description

Computes the proportion of subjects surpassing the threshold, either improvement or deterioration, in each anchor group. This can then be passed as a caption to the eCDF plot.

Usage

compute_prop_surp(
  dat = NULL,
  anchor.group = NULL,
  time.var = NULL,
  timepoint = NULL,
  change.score = NULL,
  mean.or.median = NULL,
  threshold.label = NULL
)

Arguments

dat	pass the dataframe
anchor.group	variable of the anchor group you want used here
time.var	variable of the Time in the dataframe - PLEASE CHECK THAT THIS IS CORRECTLY ORDERED, default is Time
timepoint	default here is to just use the final timepoint, e.g., "Time_4". Please be sure to have ordered your time variable correctly.
change.score	the PRO change score you want the threshold computed on
mean.or.median	pick a threshold type
threshold.label	optional numeric value, threshold to pass; default is default is "Improved_1" if "Improved" and "Deteriorated_1" if "Deteriorated"
threshold.type	character, either Improved or Deteriorated

Value

list containing a (1) a table of the proportion of subjects in each anchor group that surpass the threshold, and (2) a character vector to be optionally used as the caption in the eCDF plot

CJangelo/COA34 documentation built on June 23, 2022, 12:10 p.m.