Creation of Objects of Class longCat
Description
Function to create objects of class longCat
.
Usage
1 
Arguments
y 
a data matrix or data frame in wide (as opposed to long) format with cases in rows and repeated observations in columns. At most, 
times 
time points used for the xaxis in plotting. Either a vector of the same length as the number of columns in 
Labels 
a vector of numeric or character labels for the response options in 
tLabels 
numeric or character labels for the time points in 
id 
An optional variable identifying or naming the rows of 
endt 
An optional variable defining how far to extend the last time point for visualization purposes. The default is 
Value
longCat
returns an object of class longCat
which is a list containing at least the following components:
data 

data.sorted 

dim 
the dimension of 
times 
the 
endt 
the 
times.sorted 
if 
endt.sorted 

labels 
the 
tLabels 
the 
factors 
a vector containing the unique values in 
IndTime 
a logical indicator of whether 
nfactors 
the number of unique values in 
sorted 
a logical indicator of whether 
ascending 
logical indicator. If 
group 
a vector of the same length as the number of rows in 
groupLabels 
a optional vector of character or numeric labels for the 
order.data 
A matrix with identification (see input 
Author(s)
Stephen Tueller
References
Tueller, S. J., Van Dorn, R. A., and Bobashev, G. V. (2013). Visualization of Categorical Longitudinal and Times Series Data. Manuscript Under Review.
See Also
longCatPlot
to plot longCat
objects created by the longCat
function.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48  # create the longcat object for Figure 2 in Tueller (2011)
times < c(1,100,200,300,400,500)
f2lc < longCat(example2cat, times)
# object summary
summary(f2lc)
# compare growth curves to longCat
par(mfrow=c(1,2), bg='cornsilk3')
longContPlot(example2cat, times, ylim=c(1,5),
main='Growth Curves', ylab='', xlab='Days')
longCatPlot(f2lc, lwd=4, main='Horizontal Line Plot', colScheme='heat')
par(mfrow=c(1,1), bg='transparent')
# illustrate individually varying times of observation and the use of endt
y < matrix(sample(1:5, 500, replace=TRUE), 100, 5)
t < matrix(runif(600, 1, 3), 100, 6)
times < cbind(t[,1], t[,1]+t[,2],
t[,2]+t[,3],
t[,3]+t[,4],
t[,4]+t[,5])
endt < t[,6]
lc < longCat(y, times=times, endt=endt)
par(mfrow=c(1,1), bg='cornsilk3', mar=c(5.1, 4.1, 4.1, 10.1), xpd=TRUE)
cols < longCatPlot(lc, legendBuffer=0, groupBuffer=0,
main='Individually Varying Times of Observation')
legend(7.5, 100, legend=lc$factors, lty=1, col=cols, lwd=2)
par(bg='transparent', mar = c(5, 4, 4, 2) + 0.1, xpd=FALSE)
## Not run:
# illustrate handling factor input
y < matrix(sample(c('1', '2', '3', '4', '5'), 500, replace=TRUE), 100, 5)
lc < longCat(y)
par(mfrow=c(1,1), bg='cornsilk3', mar=c(5.1, 4.1, 4.1, 8.1), xpd=TRUE)
cols < longCatPlot(lc, legendBuffer=0)
legend(6, 100, legend=lc$factors, lty=1, col=cols, lwd=2)
par(bg='transparent', mar = c(5, 4, 4, 2) + 0.1, xpd=FALSE)
# illustrate plotting with more than 9 categories
# (a warning is issued) and the use of endt
y < matrix(sample(1:18, 500, replace=TRUE), 100, 5)
lc < longCat(y, endt=.5)
par(mfrow=c(1,1), bg='cornsilk3', mar=c(5.1, 4.1, 4.1, 8.1), xpd=TRUE)
cols < longCatPlot(lc, legendBuffer=0)
legend(6, 100, legend=lc$factors, lty=1, col=cols, lwd=2)
par(bg='transparent', mar = c(5, 4, 4, 2) + 0.1, xpd=FALSE)
## End(Not run)
