Error Bars In R Plot
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Error.bar Function R
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Hmisc R
following plot in R? Points, shown in the plot are the averages, and their ranges correspond to minimal and maximal values. I have data in two files (below is an example). x y 1 0.8773 1 0.8722 1 0.8816 1 0.8834 1 0.8759 1 0.8890 1 0.8727 2 0.9047 2 0.9062 2 0.8998 2 0.9044 2 0.8960 .. ... r plot share|improve this question edited Oct 23 '12 at 15:10 Roland
R Package Hmisc
73.2k463102 asked Oct 23 '12 at 14:29 sherlock85 1521313 Since you clearly don't want a boxplot, I changed the title of your question in order to reflect what you really want. –Roland Oct 23 '12 at 15:11 1 also plotrix::plotCI, gplots::plotCI, library("sos"); findFn("{error bar}") –Ben Bolker Oct 23 '12 at 17:29 add a comment| 5 Answers 5 active oldest votes up vote 52 down vote accepted First of all: it is very unfortunate and surprising that R cannot draw error bars "out of the box". Here is my favourite workaround, the advantage is that you do not need any extra packages. The trick is to draw arrows (!) but with little horizontal bars instead of arrowheads (!!!). This not-so-straightforward idea comes from the R Wiki Tips and is reproduced here as a worked-out example. Let's assume you have a vector of "average values" avg and another vector of "standard deviations" sdev, they are of the same length n. Let's make the abscissa just the number of these "measurements", so x <- 1:n. Using these, here come the plotting commands: plot(x, avg, ylim=range(c(avg-sdev, avg+sdev)), pch=19, xlab="Measurements", ylab="Mean +/- SD", main="Scatter plot with std.dev error bars" ) # hack: we draw arrows but with very special "arrowheads" arrows(x, avg-sdev, x, avg+sdev,
error bars Two within-subjects variables Note about normed means Helper functions Problem You want to plot means and error bars for a dataset. Solution To make graphs with error bars in r barplot ggplot2, the data must be in a data frame, and in “long”
R Summaryse
(as opposed to wide) format. If your data needs to be restructured, see this page for more information. Sample error bars in ggplot2 data The examples below will the ToothGrowth dataset. Note that dose is a numeric column here; in some situations it may be useful to convert it to a factor. http://stackoverflow.com/questions/13032777/scatter-plot-with-error-bars class="n">tg <- ToothGrowth head(tg) #> len supp dose #> 1 4.2 VC 0.5 #> 2 11.5 VC 0.5 #> 3 7.3 VC 0.5 #> 4 5.8 VC 0.5 #> 5 6.4 VC 0.5 #> 6 10.0 VC 0.5 library(ggplot2) First, it is http://cookbook-r.com/Graphs/Plotting_means_and_error_bars_(ggplot2)/ necessary to summarize the data. This can be done in a number of ways, as described on this page. In this case, we’ll use the summarySE() function defined on that page, and also at the bottom of this page. (The code for the summarySE function must be entered before it is called here). # summarySE provides the standard deviation, standard error of the mean, and a (default 95%) confidence interval tgc <- summarySE(tg, measurevar="len", groupvars=c("supp","dose")) tgc #> supp dose N len sd se ci #> 1 OJ 0.5 10 13.23 4.459709 1.4102837 3.190283 #> 2 OJ 1.0 10 22.70 3.910953 1.2367520 2.797727 #> 3 OJ 2.0 10 26.06 2.655058 0.8396031 1.899314 #> 4 VC 0.5 10 7.98 2.746634 0.8685620 1.964824 #> 5 VC 1.0 10 16.77 2.515309 0.7954104 1.799343 #> 6 VC 2.0 10 26.14 4.797731 1.5171757 3.432090 Line graphs After the data is summarized, we can make the graph. These are basic
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boxplot to summarize distributions. Means and standard errors are calculated from the raw data using describe. Alternatively, plots of means +/- one standard deviation may be drawn. Usage error.bars(x,stats=NULL, ylab = "Dependent Variable",xlab="Independent Variable", main=NULL,eyes=TRUE, ylim = NULL, xlim=NULL,alpha=.05,sd=FALSE, labels = NULL, pos = NULL, arrow.len = 0.05,arrow.col="black", add = FALSE,bars=FALSE,within=FALSE, col="blue",...) Arguments x A data frame or matrix of raw data stats Alternatively, a data.frame of descriptive stats from (e.g., describe) ylab y label xlab x label main title for figure ylim if specified, the limits for the plot, otherwise based upon the data xlim if specified, the x limits for the plot, otherwise c(.5,nvar + .5) eyes should 'cats eyes' plots be drawn alpha alpha level of confidence interval – defaults to 95% confidence interval sd if TRUE, draw one standard deviation instead of standard errors at the alpha level labels X axis label pos where to place text: below, left, above, right arrow.len How long should the top of the error bars be? arrow.col What color should the error bars be? add add=FALSE, new plot, add=TRUE, just points and error bars bars bars=TRUE will draw a bar graph if you really want to do that within should the error variance of a variable be corrected by 1-SMC? col color(s) of the catseyes. Defaults to blue. ... other parameters to pass to the plot function, e.g., typ="b" to draw lines, lty="dashed" to draw dashed lines Details Drawing the mean +/- a confidence interval is a frequently used function when reporting experimental results. By default, the confidence interval is 1.96 standard errors of the t-distribution. If within=TRUE, the error bars are corrected for the correlation with the other variables by reducing the variance by a factor of (1-smc). This allows for comparisons between variables. The error bars are normally calculated from the data using the describe function. If, alternatively, a matrix of statistics is provided with column headings of values, means, and se, then those values will be used for the plot (using the stats option). However, in this case, the error bars will be one