Reputation: 37
I am trying to add x and y axis error bars to each individual point in a scatter plot. Each point represents a standardized mean value for fitness for males and females (n=33).
I have found the geom_errorbar and geom_errorbarh functions and this example
ggplot2 : Adding two errorbars to each point in scatterplot
However my issue is that I want to specify the standard error for each point (which I have already calculated) from another column in my dataset which looks like this below
line MaleBL1 FemaleBL1 BL1MaleSE BL1FemaleSE
3 0.05343516 0.05615977 0.28666600 0.3142001
4 -0.53321642 -0.27279609 0.23929438 0.1350793
5 -0.25853484 -0.08283566 0.25904025 0.2984323
6 -1.11250479 0.03299387 0.23553281 0.2786233
7 -0.14784506 0.28781883 0.27872358 0.2657080
10 0.38168220 0.89476555 0.25620796 0.3108585
11 0.24466921 0.14419021 0.27386482 0.3322349
12 -0.06119015 1.42294820 0.32903199 0.3632367
14 0.38957538 1.66850680 0.30362671 0.4437925
15 0.05784842 -0.12453429 0.32319116 0.3372879
18 0.71964923 -0.28669563 0.16336556 0.1911489
23 0.03191843 0.13955703 0.34522310 0.1872229
28 -0.04598340 -0.35156017 0.27001451 0.1822967
'line
' is the population (n=10 individuals in each) from where each value comes from my x,y variables are 'MaleBL1
' & 'FemaleBL1
' and the standard error for each populations for males and females respectively 'BL1MaleSE
' & 'BL1FemaleSE
'
So far code wise I have
p<-ggplot(BL1ggplot, aes(x=MaleBL1, y=FemaleBL1)) +
geom_point(shape=1) +
geom_smooth(method=lm)+ # add regression line
xmin<-(MaleBL1-BL1MaleSE)
xmax<-(MaleBL1+BL1MaleSE)
ymin<-(FemaleBL1-BL1FemaleSE)
ymax<-(FemaleBL1+BL1FemaleSE)
geom_errorbarh(aes(xmin=xmin,xmax=xmax))+
geom_errorbar(aes(ymin=ymin,ymax=ymax))
I think the last two lines are wrong with specifying the limits of the error bars. I just don't know how to tell R where to take the SE values for each point from the columns BL1MaleSE
and BL1FemaleSE
Any tips greatly appreciated
Upvotes: 1
Views: 5429
Reputation: 132576
You really should study some tutorials. You haven't understood ggplot2 syntax.
BL1ggplot <- read.table(text=" line MaleBL1 FemaleBL1 BL1MaleSE BL1FemaleSE
3 0.05343516 0.05615977 0.28666600 0.3142001
4 -0.53321642 -0.27279609 0.23929438 0.1350793
5 -0.25853484 -0.08283566 0.25904025 0.2984323
6 -1.11250479 0.03299387 0.23553281 0.2786233
7 -0.14784506 0.28781883 0.27872358 0.2657080
10 0.38168220 0.89476555 0.25620796 0.3108585
11 0.24466921 0.14419021 0.27386482 0.3322349
12 -0.06119015 1.42294820 0.32903199 0.3632367
14 0.38957538 1.66850680 0.30362671 0.4437925
15 0.05784842 -0.12453429 0.32319116 0.3372879
18 0.71964923 -0.28669563 0.16336556 0.1911489
23 0.03191843 0.13955703 0.34522310 0.1872229
28 -0.04598340 -0.35156017 0.27001451 0.1822967", header=TRUE)
library(ggplot2)
p<-ggplot(BL1ggplot, aes(x=MaleBL1, y=FemaleBL1)) +
geom_point(shape=1) +
geom_smooth(method=lm)+
geom_errorbarh(aes(xmin=MaleBL1-BL1MaleSE,
xmax=MaleBL1+BL1MaleSE),
height=0.2)+
geom_errorbar(aes(ymin=FemaleBL1-BL1FemaleSE,
ymax=FemaleBL1+BL1FemaleSE),
width=0.2)
print(p)
Btw., looking at the errorbars you should probably use Deming regression or Total Least Squares instead of OLS regression.
Upvotes: 4