sorter: General Sorting Function

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

General Sorting Function

Description

A function to sort an longCat object created by longCat. sorter must be used directly when stratified plots of subgroups are desired, or when sorting other than the default is desired. Otherwise, sorter is used internally with the defaults by longCatPlot if lc$sorted=FALSE. If an object has already been sorted (lc$sorted=TRUE), sorter will not resort it but will print a code example of how to use multiple sortings.

Usage

sorter(
  lc,
  ascending = TRUE,
  whichColumns = NULL,
  num = TRUE,
  mindur = NULL,
  igrpt = FALSE,
  customSort = NULL,
  initFirst = FALSE,
  group = NULL,
  groupLabels = NULL,
  ggap = NULL
)

Arguments

lc	An object of class longCat created by longCat.
ascending	Logical indicating if sorting should be done in ascending order. Default is TRUE.
whichColumns	A numeric vector indicating which columns in lc$y should be used for sorting (e.g., c(1, 5, 7)). Useful if an intervention occurs after data collection has started and the user is not interested in sorting based on pre-intervention observations.
num	See makePatterns for details.
mindur	See makePatterns.
igrpt	Should sorter ignore repeated values for each row in lc$y for sorting purposes? See norpt.
customSort	A vector of the same length as the number of rows in lc$y providing a user-defined variable on which to sort the data prior to secondarily applying the default sort. If group is not NULL, group will be sorted prior to the customSort variable.
initFirst	If customSort is not NULL, setting initFirst=TRUE will sort on initial values prior to the custom sorting variable.
group	A vector indicating group membership, of the same length as the number of rows in lc$y. Default is NULL.
groupLabels	Numeric or character labels for the groups specified in group. Default is NULL.
ggap	A number between zero and one indicating the proportion of blank rows to be plotted between groups when group is specified. The default of NULL is set to 0.05 when groups are present, and 0.0 when there are no groups.

Value

Returns an object of class longCat where lc$sorted=TRUE.

Author(s)

Stephen J. 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

longCat and longCatPlot for further functionality.

Examples

### create a plot like that in Figure 3 from Tueller, Van Dorn, & Bobashev (2016)
par(mfrow=c(1,2), bg='cornsilk3')
times <- c(1,100,200,300,400,500,600)
f3lc <- longCat(example3, times); f3lc$sorted <- TRUE; f3lc$y.sorted <- f3lc$y
longCatPlot(f3lc, main='Unsorted', colScheme='heat', lwd=2, legendBuffer=.2)
f3lc <- longCat(example3, times)
longCatPlot(f3lc, main='Sorted', colScheme='heat', lwd=2, legendBuffer=.2)

### sort with a grouping variable and plot
par(mfrow=c(1,1), bg='cornsilk3', mar=c(5.1, 4.1, 4.1, 9.1), xpd=TRUE)
times <- c(1,100,200,300,400,500,600)
lc <- longCat(example3, times)
group <- sample(1:3, nrow(example3), replace=TRUE)
grouplc <- sorter(lc, group=group, groupLabels=1:3)
cols <- longCatPlot(grouplc, groupBuffer=.15, main='Grouped Data', colScheme='heat',
                    lwd=2, legendBuffer=0)
legend(610, 130, legend=1:5, col=cols, lty=1, lwd=2)
par(bg='transparent', mar = c(5, 4, 4, 2) + 0.1, xpd=FALSE)

### using the sorted data from the previous plot, repeate using ggplot2
#   following the example of Figure 4 of bdemarest's answer on
#   https://stackoverflow.com/questions/11513149/
#   good-ways-to-visualize-longitudinal-categorical-data-in-r/
grouplc.df <- data.frame(id=1:nrow(grouplc$group.sorted),
                         group=grouplc$group.sorted[,1], grouplc$y.sorted)
grouplc.long <- reshape(grouplc.df,
                        varying = names(grouplc$y.sorted),
                        v.names = "score",
                        timevar = "time",
                        times = times[1:ncol(grouplc$y.sorted)],
                        direction = "long")
grouplc.long$score <- factor(grouplc.long$score)
grouplc.long$group <- factor(grouplc.long$group, level=3:1)
# remove NA's introduced using group option in sorter
grouplc.long <- na.omit(grouplc.long)
library(ggplot2)
ggplot(grouplc.long, aes(x=time, y=id, fill=score)) +
  geom_tile(colour="transparent") +
  scale_fill_manual(values=cols) +
  facet_grid(group ~ ., space="free_y", scales="free_y")

### sort with a grouping variable and events and plot
times <- c(1,100,200,300,400,500,600)
set.seed(45962)
events <- matrix(sample(1:3, nrow(example3)*2, replace=TRUE), nrow(example3), 2)
set.seed(23498)
event.times <- matrix(sample(min(times):max(times), nrow(example3)*2, replace=TRUE),
                      nrow(example3), 2)
labels <- c('Street', 'Drug Tx', 'Jail', 'Prison', 'Unknown')
eventLabels=c('Arrest', 'Drug Test', 'Hearing')
eventlc <- longCat(example3, times=times, Labels=labels,
                   events=events, event.times=event.times,
                   eventLabels=eventLabels)
set.seed(4290)
groupevent <- sample(1:3, nrow(example3), replace=TRUE)
groupeventlc <- sorter(eventlc, group=groupevent)
par(mfrow=c(1,1), bg='cornsilk3', mar=c(5.1, 4.1, 4.1, 12.1), xpd=TRUE)
cols <- longCatPlot(groupeventlc, legendBuffer=0, groupBuffer=0.15,
                    main='Grouping and Events')
legend(610, 130, legend=groupeventlc$Labels, lty=1, col=cols, lwd=2)
legend(610, 60, legend=groupeventlc$eventLabels,
       pch=1:length(groupeventlc$eventLabels))
par(bg='transparent', mar = c(5, 4, 4, 2) + 0.1, xpd=FALSE)

stueller/longCatEDA documentation built on March 9, 2024, 4:08 a.m.