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POAutomatic grouping of treatments in graph by significant differences in r
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  1. POAutomatic grouping of treatments in graph by significant differences in r
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    copied!<p>In my work I often have to make different treatment comparisons using Anova and Tukey tests to determine which of multiple treatments in one factor experiments are statistically distinct from one another. </p> <p>The code I have attached yields two separate <a href="http://imgur.com/a/fkalq" rel="nofollow">figures</a>: one with treatment distribution of values (example graph1) and another with the Tukey test results showing which pair of treatments are significantly different from one another (example graph2). </p> <p>What I have done in the past is to look at the Tukey results and manually edit the first graph with letters indicating groups of statistically equivalent groups (example graph3). I have been looking at different r libraries for ways to automatically produce something similar to graph 3 that summarizes such groupings but have not yet found a way. Does anyone have any suggestions?</p> <p>PS- I am sorry if the graph routine below is a little cumbersome, but it is essentially a fragment of a much more comprehensive set of functions that I have developed to test data distribution, conditionally apply relevant tests and produce output tables and figures. </p> <p>The code I have written to make the first two graphs is below. t?usp=sharing</p> <pre><code>Group=c("G1","G1","G1","G1","G2","G2","G2","G2","G3","G3","G3","G3") Vals=c(runif(4),runif(4)+0.5,runif(4)+0.1) data=data.frame(Group) data=cbind(data, Vals) anova_results=aov(Vals~Group,data=data) anova_results2=anova(anova_results)[1, ] anova_significance=anova_results2[1,"Pr(&gt;F)"] significant=anova_significance[1]&lt;=0.05 if (significant==1) { Tukey_results=TukeyHSD(anova_results,"Group") Tukey_results=Tukey_results$Group } plot(data$Group, data$Vals) if (significant==1) { plot(TukeyHSD(anova_results,"Group"), las=1) } </code></pre>
 

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