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,add=FALSE,
    colors=NULL,col.arrows=NULL,col.text=NULL,...)

### 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)
`add` | if TRUE, overlay the values with a prior plot
`colors` | What color(s) should be used for the plot character? Defaults to black
`col.arrows` | What color(s) should be used for the arrows – defaults to colors
`col.text` | What color(s) should be used for the text – defaults to colors
`...` | 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

### See Also

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","green","blue")
    films <- c("Sad","Horror","Neutral","Happy")
    affect.mat <- describeBy(affect[10:17],affect$Film,mat=TRUE)
     error.crosses(affect.mat[c(1:4,17:20),],affect.mat[c(5:8,21:24),],
        labels=films[affect.mat$group1],xlab="Energetic Arousal",
         ylab="Tense Arousal",colors =
         colors[affect.mat$group1],pch=16,cex=2)

[Package psych version 1.6.9 Index]