[R] How to produce serveral plots with pairs of vectors

[slyrs66]

Thank you, David.

What I actually would like to do in an more "elegant" way is the following

boxplot (meinspss$attr_diff_gesamt ~ meinspss$R1_02)
boxplot (meinspss$finanz_diff_gesamt ~ meinspss$R2_02)
boxplot (meinspss$leist_diff_gesamt ~ meinspss$R3_02)
boxplot (meinspss$soz_diff_gesamt ~ meinspss$R4_02)
boxplot (meinspss$wert_diff_gesamt ~ meinspss$R5_02)

As the final code is much more complicated (see below) I was looking for a
loop oder lapply() way to do it

Thanks gain for you help.

Andrew

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
with (meinspss, {
beanplot(dimension ~ gruppe, ll=0.04, what=c(1,1,1,1), jitter = 1.2, 
main = titel, ylab="Differenzwert", names = c("Aufwärts", "Lateral",
"Abwärts" ),
overalline = "mean", beanlines = "median", col=c("orange","yellow","bisque",
"white"))

## Run boxplot to find statistics, but don't draw the boxplots
S <- boxplot(dimension ~ gruppe, names = c("Aufwärts", "Lateral",
"Abwärts"), plot=FALSE)
## Define locations for additional chart elements
at <- c(1:length(S$names))

means <- by(dimension, gruppe, mean, na.rm=TRUE)
points(at,means, pch = 23, cex = 1.2, bg = "blue")

## Draw Mean values to the left edge of each violinplot
text(at - 0.3, means, labels = formatC(means, format = "f", digits = 1),
    pos = 2, cex = 1, col = "blue")

## Draw Median values to the right edge of each violinplot
text(at + 0.3, S$stats[3, ], labels = formatC(S$stats[3, ],
     format = "f", digits = 1), pos = 4, cex = 1, col = "darkgreen")
     
     ##-  Get CIs -##
## create standard error function--
se <- function(x) {
         y <- x[!is.na(x)]
         sqrt(var(as.vector(y))/length(y))
    }
## create length function for non-missing values
lngth <- function(x){
            y <- x[!is.na(x)]
            length(y)
    }
## Compute vectors of standard error and n
Hse <- by(dimension, gruppe,se)
Hn  <- by(dimension, gruppe,lngth)
## compute 95% CIs and store in vectors
civ.u <- means + qt(.975, df=Hn-1) * Hse # Upper bound CI
civ.l <- means + qt(.025, df=Hn-1) * Hse # Lower bound CI
## Draw CI, first vertical line, then upper and lower horizontal
segments(at, civ.u, at, civ.l, lty = "solid", lwd = 2, col = "red")
segments(at - 0.1, civ.u, at + 0.1, civ.u, lty = "solid", lwd =2,col =
"red")
segments(at - 0.1, civ.l, at + 0.1, civ.l, lty = "solid", lwd =2,col =
"red")

## Print "n" under the name of measure
mtext(S$n, side = 1, at = at, cex=.75, line = 2.5)
mtext(S$names, side = 1, at = at, cex=1, line = 1)
})

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