'Using ggplot for confidence intervals display
I've got to build a plot of mean values and 99% confidence intervals (based on t-distribution) of data set cuckoos from package DAAG.
Here is my solution
ggplot(data=cuckoos, aes(x=species, y=length, colour=species)) +
stat_summary(geom='pointrange', fun.args = list(mult=1)) +
theme_dark() +
theme(legend.position="none",
axis.text = element_text(size=10),
axis.text.x = element_text (angle = 45, hjust = 1)) +
scale_colour_brewer(palette = "Pastel1") +
coord_cartesian(ylim=c(21,24))
The confidence intervals of the resulting plot do not match the right answer (see the images attached). What the problem might be?
Solution 1:[1]
The default function of the stat_summary
function is mean_se
, meaning that you're actually getting the mean and a standard deviation. If you want to calculate the 99% confidence interval, you need to use the mean_cl_normal
function and specify that you want to get the 0.99 confidence interval, instead of the default 0.95.
ggplot(data= DAAG::cuckoos, aes(x=species, y=length, colour=species)) +
stat_summary(geom='pointrange', fun.data = "mean_cl_normal", fun.args = list(conf.int = 0.99)) +
theme_dark() +
theme(legend.position="none", axis.text = element_text(size=10), axis.text.x = element_text (angle = 45, hjust = 1)) +
scale_colour_brewer(palette = "Pastel1") +
coord_cartesian(ylim=c(21,24))
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
Solution | Source |
---|---|
Solution 1 | Sergio Romero |