Scheirer-Ray-Hare test in R

See how to carry out the Scheirer-Ray-Hare test in R.
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This video relates to section 11.7 in the book Research Methods for the Biosciences third edition by Debbie Holmes, Peter Moody, Diana Dine, and Laurence Trueman. The video is narrated by Laurence Trueman.
© Oxford University Press

[@takheru]

Hi there, is there a possibility to run a post hoc test on the data? Cheers, Boo

[@danilor.a.dealmeida8492]

Hello, thank for the video. If you test without ranking the data, the results are the same. Below the script: #---------------------------------------------------------------------------------------------# bellis = c(1, 2.5, 2.5, 4, 5, 6.5, 6.5, 9.5, 8,9.5, 12, 12, 14.5, 12, 14.5, 16) location = rep(c("Cricket", "Lawn"), each = 8) fertiliser = rep(c("no", "yes", "no", "yes"), each = 4) aov.r = aov(bellis ~ location*fertiliser) summary(aov) #Extract the sum of squares df = anova(aov.r)[,"Df"] sum_df = sum(df) ss = anova(aov.r)[, "Sum Sq"] sum_ss = sum(ss) #Calculate que MS value MS = sum_ss/sum_df #calculate H value H_bellis = SS[1]/MS H_fertiliser = SS[2]/MS H_interaction = SS[3]/MS #convert this in probability 1-pchisq(H_bellis, df[1]) 1-pchisq(H_fertiliser, df[2]) 1-pchisq(H_interaction, df[1]) #---------------------------------------------------------------------------------------------# In this case, you do not need to rank. Is correct? thanks, Danilo.