# Exercise 9.8 # Statistical Methods in Biology: Design and Analysis of Experiments and Regression # by S.J. Welham, S.A. Gezan, S.J. Clark & A. Mead (2014) # Chapman & Hall/CRC Press, Boca Raton, Florida. ISBN: 978-1-4398-0878-8 # Data from S Foster, Rothamsted Research # Version 1, 01/08/2015 # Set working directory - use setwd() function or from Session menu in RStudio # e.g. setwd("d:/stats4biol/data) # load external packages - available from CRAN library(ggplot2) # Read data & assign factors simulator <- read.table('simulator.dat', sep="", header=TRUE) simulator$Expt <- as.factor(simulator$Expt) simulator$DSimulator <- as.factor(simulator$DSimulator) simulator$Plant <- as.factor(simulator$Plant) simulator$DCage <- as.factor(simulator$DCage) summary(simulator) # Plot data qplot(data=simulator, y=Nymphs, x=Treatment, colour=Clone, facets=Expt~.) # Multi-stratum ANOVA simulator.msaov <- aov(Nymphs ~ Treatment*Clone+Error(Expt/DSimulator/Plant/DCage), data=simulator) summary(simulator.msaov) # Tables of means - not possible to get SEDs?? model.tables(simulator.msaov, type="means") # Equivalent single-stratum ANOVA (wrong variance ratios) to get residuals simulator.aov <- aov(terms(Nymphs ~ Expt + Treatment + Expt:DSimulator/Plant + Clone/Treatment, keep.order=TRUE), data=simulator) summary(simulator.aov) # Residual plots plot(simulator.aov, ask=FALSE) hist(residuals(simulator.aov)) # End of file