longContPlot: Plot Continuous Longitudinal Data

In longCatEDA: Package for Plotting Categorical Longitudinal and Time-Series Data

Description

Function to plot continuous longitudinal or time-series data.

Usage

longContPlot(y, times = NULL, jog=FALSE, ylim = NULL, xlim = NULL, ...)

Arguments

y	a data matrix or data frame in wide (as opposed to long) format with cases in rows and repeated observations in columns.
times	time points used for the x-axis in plotting. Either a vector of the same length as the number of columns in y (i.e., all cases have the same times of observation), or a matrix of the same dimension as y (i.e., individually varying times of observation). Default is NULL and is assigned the value 1:ncol(y).
jog	When y is integer data, it can be useful to jog all values by a small amount. When jog=TRUE, a random uniform variate in [-.25, .25] is added to each row in y.
ylim	see par. Default is NULL and calculated from y.
xlim	see par. Default is NULL and calculated from y.
...	Arguments to be passed to plot. See par.

Author(s)

Stephen Tueller

References

Tueller, S. J., Van Dorn, R. A., & Bobashev, G. V. (2016). Visualization of categorical longitudinal and times series data (Report No. MR-0033-1602). Research Triangle Park, NC: RTI Press. http://www.rti.org/publication/visualization-categorical-longitudinal-and-times-series-data

See Also

longCatPlot.

Examples

# longitudinal plot
times <- c(1,100,200,300,400,500)
par(mfrow=c(1,1), bg='cornsilk3')
longContPlot(example2cont, times, ylim=c(-2,6), main='', ylab='', xlab='Day')
par(mfrow=c(1,1), bg='transparent')

# jogging example
times <- c(1,100,200,300,400,500)
par(mfrow=c(1,2), bg='cornsilk3')
longContPlot(example2cat, times,           ylim=c(0,6), 
  main='Growth Curves', ylab='', xlab='Days')
longContPlot(example2cat, times, jog=TRUE, ylim=c(0,6), 
  main='Growth Curves + Jogging', 
	ylab='', xlab='Days')
par(mfrow=c(1,1), bg='transparent')# compare growth curves to longCat

longCatEDA documentation built on May 2, 2019, 7:33 a.m.