graph.CL {SCVA}

Plot a measure of central tendency

Description

A measure of central tendency ((trimmed) mean, (broadened) median, M-estimator) is plotted as a horizontal reference line superimposed on the raw time series data.

Usage

graph.CL(design,CL,tr,data=read.table(file.choose(new=FALSE)),xlab="Measurement Times",
ylab="Scores",ylim=NULL,legendxy=NULL,labels=c("A","B","A","B"))

Arguments

design

Type of single-case design: "AB", "ABA", "ABAB", "CRD"(completely randomized design), "RBD" (randomized block design), "ATD" (alternating treatments design), "MBD" (multiple-baseline AB design) or "Custom" (user specified design).

CL

Measure of central tendency: "mean", "median", "bmed" (broadened median), "trimmean" (trimmed mean), or "mest" (M-estimator of location).

tr

If CL="trimmean": the percentage of observations that has to be removed from the end of the distribution before computing the mean. It can be any value from 0 (regular arithmetic mean) to 0.5. Usually 20 percent of the observations is trimmed (so tr=0.2). If CL="mest": the desired value for the constant K. Usually a percentile of the standard normal distribution is chosen. Wilcox (2005) suggests using K=1.28, which corresponds to the 90th percentile of the standard normal distribution and covers 80 percent of the underlying distribution.

data

File in which the data can be found. Default: a window pops up in which the file can be selected.

xlab

Label x axis.

ylab

Label y axis.

ylim

Y axis limits in the form c(min, max).

legendxy

Optional legend location x and y coordinates in the form c(x coordinate, y coordinate). Only used when design is "CRD", "RBD", "ATD" or "Custom".

labels

Optional labels for treatment levels in the form c("A", "B").

Details

When using the default data argument, a window will pop up to ask in what file the data can be found. This text file containing the data should consist of two columns for single-case phase and alternation designs: the first with the condition labels and the second with the obtained scores. For multiple-baseline designs it should consist of these two columns for EACH unit. This way, each row represents one measurement occasion. It is important not to label the rows or columns.

Missing data should be indicated as NA. For calculations, missing data are omitted. Please note that some of the complicated plots may not work if there is missing data.

For alternation designs, after the plot is drawn, the location of the legend should be indicated by a left mouse click.

Note

For the calculation of the M-estimator of location, the function mest(x,bend=1.28) from Wilcox (2005) is used.

Wilcox, R.R. (2005). Introduction to robust estimation and hypothesis testing (2nd ed.). San Diego, CA: Elsevier Academic Press.

References

Bulte, I., & Onghena, P. (2012). When the truth hits you between the eyes: A software tool for the visual analysis of single-case experimental data. Methodology, 8, 104-114.

http://ppw.kuleuven.be/home/english/research/mesrg

See Also

graph to simply plot raw single-case data.

graph.VAR to display variability information.

graph.TREND to display a possible trend in the data.

graphly to display an interactive plot.

Examples

data(AB)
graph.CL(design = "AB", CL = "mean", data = AB)