diffFunction: Function for finding differences between different factor...

In jbirstler/biostatrpts: Functions for UW-Biostatistics Report Creation

Description

This function is meant for finding differences between different factor levels for the same patient for either numeric or ordinal variables. It can be used inside the AEfactorized() and uwLeveledBoxPlot by setting delta=TRUE, or by itself

Usage

diffFunction(
  Diffdata,
  variable,
  TrxName,
  VisitName,
  Baseline,
  ptID,
  deltaPct = FALSE
)

Arguments

Diffdata	Name of data set in R
variable	String of variable name of interest in Diffdata
TrxName	String of treatment variable name in Diffdata
VisitName	String of variable name for time points
Baseline	String of level name in VisitName to be used as baseline
ptID	String of variable name for Identification Numbers
deltaPct	Logical. TRUE gives percentage change from baseline

Value

A data frame is returned with difference column, time column, treatment column, and ID column.

Differences are set so the baseline value is being subtracted from the non-baseline value.

Author(s)

University of Wisconsin-Madison Biostatistics and Medical Informatics Department, Scott Hetzel M.S. Assistance from Frontier Science and Technology Reseach Foundation, Pat Lenon and Zekai Otles.

See Also

AEfactorized(), uwLeveledBoxPlot()

Examples

# Example

ID <- rep(letters[1:20], 3)
TRT <- rep(c("A", "B"), 30)
Time <- c(rep("Baseline", 20), rep("Week 5", 20), rep("Week 10", 20))
Time <- ordered(Time, c("Baseline", "Week 5", "Week 10"))
AE <- sample(c(1, 2, 3, 4), 60, replace = TRUE)

data2 <- data.frame(ID, TRT, Time, AE)

diffFunction(
  Diffdata = data2,
  variable = "AE",
  TrxName = "TRT",
  VisitName = "Time",
  Baseline = "Baseline",
  ptID = "ID",
  deltaPct = TRUE
)

jbirstler/biostatrpts documentation built on May 7, 2020, 12:10 a.m.