I've been looking into using planned contrasts as opposed to post-hoc t-tests. I typically use ezANOVA (Type III ANOVA) but it seems that conducting planned contrasts using ezANOVA is not currently...

I have a large dataset which I would like to perform post hoc computation: dat = as.data.frame(matrix(runif(10000*300), ncol = 10000, nrow = 300)) dat$group = rep(letters[1:3], 100) Here is my ...

I'm trying to create a boxplot with ggplot of a count (MedMean) on yaxis and various independent samples (Site_Name) on xaxis. ggplot(medianlist,aes(x=reorder(Site_Name,MedMean,FUN=median),y=MedMea...

I fitted a proportional odds cumulative logit model on ordinal data using MASS's polr function using (in this case on data giving the preference for different kinds of cheese) : data=read.csv("htt...

I fitted a mutinomial model using nnet's multinom function using (in this case on data giving the diet preference of male and female and different size classes of alligators in different lakes) : ...

I have an experiment that is unbalanced where at three sites (L, M, H) we measure a parameter (met) in four different vegetation types (a, b, c, d). All vegetation types are present at all three si...

I am trying to understand how to work with ANOVAs and post-hoc tests in R. So far, I have used aov() and TukeyHSD() to analyse my data. Example: uni2.anova <- aov(Sum_Uni ~ Micro, data= uni2) ...

If I have some data and do an ANOVA and post-hoc tests, how do I make a boxplot that adds the post-hoc classification automatically, rather than having to edit the figure outside of R? For example...