Barplot mean /w SD in R-Project

Question

Sounds like a trivial one, but some research didn´t come up with an elegant solution: I have a dataframe structured with a categorial variable (GROUP) and a continuous read-out variable (bloodpressure). How can a make a simple box-plot showing the mean for each group with its standard deviation? There are multiple groups: A,B,C,D How can I perform an ANOVA post-hoc analysis within the dataframe. How does it work with Mann-Whitney-U-Test? Can I mark the significance level in the bar-plot? How can I streamline this operation to multiple continuous variables (dia_bloodpressure, sys_bloodpressure, mean_bloodpressure) and sink() the output in different files (by name of the variable)?

Answer 1

After some research I came up with the agricolae package. This one provides multiple group comparison. The resulting objects can be pipelined into a decent plotting function for groupwise bar-graphs +/- SD or SEM. Unfortunately, no way to use markers of significance between groups in the plots.

Answer 2

After some more programming in R, I stumbled over another nice package suitable for medical research: psych. Considering the question above, describe() and describeBy() get statistical overview of a dataframe and sort it by a grouping variable. The function error.bars.by() is an advanced plotting function for mean values +/- SD. The package offers many functions on covariate analysis, which are useful in psychological research but might also help for medical and marketing research.

Answer 3

A possible code snippet:

library(psych)

x<-c(1,2,3,4,5,6,7,8,9,NA)
y<-c(2,3,NA,3,4,NA,2,3,NA,2)
group<-rep((factor(LETTERS[1:2])),5)
df<-data.frame(x,y,group)
df

by(df$x,df$group,summary)
by(df$x,df$group,mean)

sd(df$x) #result: NA
sd(df$x, na.rm=TRUE) #result: 2.738613

v = c("x", "y")#or
v = colnames(df)[1:2]
sapply(v, function(i) tapply(df[[i]], df$group, sd, na.rm=TRUE))

describeBy(df$x, df$group)

error.bars.by(df$x, df$group, bars=TRUE)