catseyes {catseyes} | R Documentation |

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.

```
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
)
```

`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) |

Clark R. Andersen crandersen@mdanderson.org

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

```
#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]