abacus.plot: Create an abacus plot Creates an abacus plot, depicting...

In IrregLong: Analysis of Longitudinal Data with Irregular Observation Times

Create an abacus plot Creates an abacus plot, depicting visits per subject over time

Description

Create an abacus plot Creates an abacus plot, depicting visits per subject over time

Usage

abacus.plot(
  n,
  time,
  id,
  data,
  tmin,
  tmax,
  xlab.abacus = "Time",
  ylab.abacus = "Subject",
  pch.abacus = 16,
  col.abacus = 1
)

Arguments

n	the number of subjects to randomly sample. Subjects are sampled without replacement and therefore n must be smaller than the total number of subjects in the dataset
time	character string indicating which column of the data contains the time at which the visit occurred
id	character string indicating which column of the data identifies subjects
data	data frame containing the variables in the model
tmin	the smallest time to include on the x-axis
tmax	the largest time to include on the x-axis
xlab.abacus	the label for the x-axis
ylab.abacus	the label for the y-axis
pch.abacus	the plotting character for the points on the abacus plot
col.abacus	the colour of the rails on the abacus plot

Details

This function creates a plot for n randomly sampled individuals from the supplied dataset, with one row per subject and one point per visit. This can be useful for visualising the extent of irregularity in the visit process. For example, with perfect repeated measures data (i.e., no irregularity), the points will line up vertically. With greater irregularity, the points will be randomly scattered over time.

Value

produces a plot depicting observation times for each subject. No values are returned

Examples

library(MEMSS)
data(Phenobarb)
Phenobarb$event <- 1-as.numeric(is.na(Phenobarb$conc))
data <- Phenobarb[Phenobarb$event==1,]
abacus.plot(n=20,time="time",id="Subject",data=data,tmin=0,tmax=16*24,
xlab.abacus="Time in hours",pch=16,col.abacus=gray(0.8))

IrregLong documentation built on March 18, 2022, 5:45 p.m.