error.crosses {psych} R Documentation

## Plot x and y error bars

### Description

Given two vectors of data (X and Y), plot the means and show standard errors in both X and Y directions.

### Usage

```error.crosses(x,y,labels=NULL,main=NULL,xlim=NULL,ylim= NULL,
xlab=NULL,ylab=NULL,pos=NULL,offset=1,arrow.len=.2,alpha=.05,sd=FALSE,...)
```

### Arguments

 `x` A vector of data or summary statistics (from Describe) `y` A second vector of data or summary statistics (also from Describe) `labels` the names of each pair – defaults to rownames of x `main` The title for the graph `xlim` xlim values if desired– defaults to min and max mean(x) +/- 2 se `ylim` ylim values if desired – defaults to min and max mean(y) +/- 2 se `xlab` label for x axis – grouping variable 1 `ylab` label for y axis – grouping variable 2 `pos` Labels are located where with respect to the mean? `offset` Labels are then offset from this location `arrow.len` Arrow length `alpha` alpha level of error bars `sd` if sd is TRUE, then draw means +/- 1 sd) `...` Other parameters for plot

### Details

For an example of two way error bars describing the effects of mood manipulations upon positive and negative affect, see http://personality-project.org/revelle/publications/happy-sad-appendix/FIG.A-6.pdf

The second example shows how error crosses can be done for multiple variables where the grouping variable is found dynamically. The `errorCircles` example shows how to do this in one step.

### Author(s)

William Revelle
revelle@northwestern.edu

To draw error bars for single variables `error.bars`, or by groups `error.bars.by`, or to find descriptive statistics `describe` or descriptive statistics by a grouping variable `describeBy` and `statsBy`.

A much improved version is now called `errorCircles`.

### Examples

```
#just draw one pair of variables
desc <- describe(attitude)
x <- desc[1,]
y <- desc[2,]
error.crosses(x,y,xlab=rownames(x),ylab=rownames(y))

#now for a bit more complicated plotting
data(bfi)
desc <- describeBy(bfi[1:25],bfi\$gender) #select a high and low group
error.crosses(desc\$'1',desc\$'2',ylab="female scores",xlab="male scores",main="BFI scores by gender")
abline(a=0,b=1)

#do it from summary statistics  (using standard errors)
g1.stats <- data.frame(n=c(10,20,30),mean=c(10,12,18),se=c(2,3,5))
g2.stats <- data.frame(n=c(15,20,25),mean=c(6,14,15),se =c(1,2,3))
error.crosses(g1.stats,g2.stats)

#Or, if you prefer to draw +/- 1 sd. instead of 95% confidence
g1.stats <- data.frame(n=c(10,20,30),mean=c(10,12,18),sd=c(2,3,5))
g2.stats <- data.frame(n=c(15,20,25),mean=c(6,14,15),sd =c(1,2,3))
error.crosses(g1.stats,g2.stats,sd=TRUE)

#and seem even fancy plotting: This is taken from a study of mood
#four films were given (sad, horror, neutral, happy)
#with a pre and post test
data(affect)
colors <- c("black","red","white","blue")