error.crosses: Plot x and y error bars

In psych: Procedures for Psychological, Psychometric, and Personality Research

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 https://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
[e-mail]

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
if(require(psychTools)){

data(psychTools::affect)
colors <- c("black","red","green","blue")
films <- c("Sad","Horror","Neutral","Happy")
affect.mat <- describeBy(psychTools::affect[10:17],psychTools::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)
}

psych documentation built on June 27, 2024, 5:07 p.m.