catseyes {catseyes} R Documentation

## catseyes

### Description

The catseyes() function is used to plot catseye interval(s) onto a an existing basic R plot background. Catseye plots illustrate the normal distribution of the mean (picture a normal bell curve reflected over its base and rotated 90 degrees), with a shaded confidence interval; they are an intuitive way of illustrating and comparing normally distributed estimates, and are arguably a superior alternative to standard confidence intervals, since they show the full distribution rather than fixed quantile bounds. The catseyes() function requires pre-calculated means and standard errors (or standard deviations), provided as numeric vectors; this allows the flexibility of obtaining this information from a variety of sources, such as direct calculation or prediction from a model – see examples below. NOTE: The drawn vertical range of the outline spans 99.8% of the distribution of the mean.

### Usage

catseyes(
x,
ymean,
yse,
dx = 0.1,
conf = 0.95,
se.only = TRUE,
col = "black",
shade = rgb(0.05, 0.05, 0.05, 0.2),
lwd = 1,
plot.mean.line = FALSE,
fTransform = NULL
)


### Arguments

 x numeric horizontal position(s); if factor, will be converted to integer in factor level order ymean numeric mean(s) yse numeric standard error(s); may use standard deviation(s) for population level plots dx specifies the width (in x direction) of the catseye interval(s) conf specifies the confidence of the confidence interval (conf=.95 for alpha=.05) se.only boolean, if TRUE (default) will shade only +/- 1 standard error about the mean, overriding conf, otherwise if FALSE will shade the confidence interval (per conf) about the mean col specifies the color of the outline of the catseye, as well as the interval point & line, if shown shade specifies the color of the shaded confidence region lwd sets the line width of the interval and outline plot.mean.line boolean, draws a horizontal line at the position of the mean if TRUE fTransform Optional function to transform catseye plot from normal distribution (as with analyzing log-tranformed data, see example under catseyesplot)

### Author(s)

Clark R. Andersen crandersen@mdanderson.org

### References

Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 27, 7-29. <doi:10.1177/0956797613504966> pmid:24220629
http://www.psychologicalscience.org/index.php/publications/observer/2014/march-14/theres-life-beyond-05.html

### Examples

#Show catseye plots for 4 groups with means of c(-3,2,-1,6)
#    and standard errors of c(1,2,4,3)
plot(NULL,xlim=c(.5,4.5),ylim=c(-10,10),xlab="",ylab="",main="4 Groups",xaxt="n")
axis(1,at=1:4,labels = c("Group1","Group2","Group3","Group4"))
catseyes(1:4,ymean=c(-3,2,-1,6),yse=c(1,2,4,3))
#Optionally, add points and lines (usually lines only when joining time sequence)
lines(1:4,c(-3,2,-1,6),type="b")


[Package catseyes version 0.2.5 Index]