Plotting confidence interval bars from summary statistics A bit like a box plot. I mean not necessarily the standard upper confidence interval, lower confidence interval, mean, and data range-showing box plots, but I mean like a box plot with just the three pieces of data: the 95% confidence interval and mean.
This is a screenshot of a journal article which had exactly what I want: 
I would also like to know how I would use the software the answerer mentions to create such a plot.
 A: In MATLAB, you might want to try the errorbar function: http://www.mathworks.de/de/help/matlab/ref/errorbar.html
Alternatively, you can do it the dumb and manual way. For example, given a matrix of data points "a", you can calculate your means using the function m = mean(a), calculate your CIs (depending on what CI you need), and plot the results by hand.
Demonstration if you already know the mean and CI, assuming CIs are in a matrix CI (first and second column) and means are in a matrix a:
plot(1:length(CI),a,'o','markersize', 10)           % plot the mean
hold on;
plot(1:length(CI),CI(1,:),'v','markersize', 6)              % plot lower CI boundary
hold on;
plot(1:length(CI),CI(2,:),'^','markersize', 6)              % plot upper CI boundary
hold on;

for I = 1:length(CI)                                        % connect upper and lower bound with a line
line([I I],[CI(1,I) CI(2,I)])
hold on;
end;

axis([0 length(CI)+1 min(CI(1,:))*0.75 max(CI(2,:))*1.25])  % scale axis

Demonstration in the case where you know individual measurements, for a repeated-measures experiment, 3+ conditions, one condition per column, one subject per line in matrix a, no missing samples, 95% CI as by MATLAB's ttest():
[H,P,CI] = ttest(a);                                        % calculate 95% CIs for every column in matrix a
                                                            % CIs are now in the matrix CI!

plot(1:length(CI),[mean(a)],'o','markersize', 10)           % plot the mean
hold on;
plot(1:length(CI),CI(1,:),'v','markersize', 6)              % plot lower CI boundary
hold on;
plot(1:length(CI),CI(2,:),'^','markersize', 6)              % plot upper CI boundary
hold on;

for I = 1:length(CI)                                        % connect upper and lower bound with a line
line([I I],[CI(1,I) CI(2,I)])
hold on;
end;

axis([0 length(CI)+1 min(CI(1,:))*0.75 max(CI(2,:))*1.25])  % scale axis

A: This type of plot in R using ggplot2, though you might have to do some fiddling with the axis font size:
library(ggplot2)
data.estimates = data.frame(
  var   = c('1', '2', '3', '4', '5', '6', '7', '8', '9'),
  par = c(1.12210,0.18489,1.22011,1.027446235,0.43521,0.53464,1.93316,-0.43806,-0.12029),
  se = c(0.42569,0.32162,0.58351,0.771608551,0.24803,0.65372,0.92717,0.45939,0.51558))
data.estimates$idr <- exp(data.estimates$par)
data.estimates$upper <- exp(data.estimates$par + (1.96*data.estimates$se))
data.estimates$lower <- exp(data.estimates$par - (1.96*data.estimates$se))

p2 <- ggplot(data.estimates, aes(var,idr, size=10)) + theme_bw(base_size=10)
p2 + geom_point() +geom_errorbar(aes(x = var, ymin = lower, ymax = upper, size=2), width = 0.2) + scale_y_log10(limits=c(0.1, 50), breaks=c(0.1, 0.5, 1, 5, 10, 25, 50)) + xlab("Site") + ylab("RR")


A: This could be done in R with points() (or plot(..., type="p")) and segments().  There might also be R functions designed to create the CI's for you, but those might require the original data. The multiple panels in the same figure created with par(mfrow=c(4,1)).  If you don't know any R, this would be hard to do easily (as in, you would have to learn a bit more R or get someone to help with your specific data set).
A: In Stata use serrbar or ciplot (SSC) or eclplot (Stata Journal, SSC). 
A: Assuming you have access to the original data you can do this in R with the lineplot.CI function in the sciplot library
Example with mtcars dataset:
lineplot.CI(x.factor=gear, response=mpg, group=vs, data=mtcars)

Note that lineplot.CI by default plots SE bars (it can be changed defining a new function with the argument ci.fun to plot 95% CI intervals)
lineplot.CI(x.factor=gear, response=mpg, group=vs, data=mtcars, ci.fun=function(x) c(mean(x)-1.96*se(x), mean(x)+1.96*se(x)))

A: Look if this helps you. R solution:
par(mfrow=c(2,1)) # to stack the charts on column

#Dataset 1

upperlimit = c(10,12,8,14)
lowerlimit = c(5,9,4,7)
mean = c(8,10,6,12)

df = data.frame(cbind(upperlimit,lowerlimit,mean))

plot(df$mean, ylim = c(0,30), xlim = c(1,4))

install.packages("plotrix")
require(plotrix)
plotCI(df$mean,y=NULL, uiw=df$upperlimit-df$mean, liw=df$mean-df$lowerlimit, err="y",      pch=20, slty=3, scol = "black", add=TRUE)

#Dataset 2

upperlimit_2 = upperlimit*1.5
lowerlimit_2 = lowerlimit*0.8
mean_2 = upperlimit_2-lowerlimit_2

df_2 = data.frame(cbind(upperlimit_2,lowerlimit_2,mean_2))

plot(df$mean_2, ylim = c(0,30), xlim = c(1,4))

plotCI(df_2$mean_2,y=NULL, uiw=df_2$upperlimit_2-df_2$mean_2, liw=df_2$mean_2-   df_2$lowerlimit_2, err="y", pch=20, slty=3, scol = "black", add=TRUE)

rm(upperlimit,lowerlimit,mean,df,upperlimit_2,lowerlimit_2,mean_2,df_2) #remove the objects stored from workspace

par(mfrow=c(1,1)) # go back to default (one graph at a time)


A: GraphPad Prism can easily make this kind of graph, plotting error bars from error values you enter. Create a grouped table formatted for entery of mean, - error and + error. 
