# Example 7.3

# 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
# Version 1, 13/08/2014

# Set working directory - use setwd() function or from Session menu in RStudio
# e.g. setwd("d:/stats4biol/data)


### Plot-level measurements

# Read data from file in working directory
oedoplot <- read.table("oedoplot.dat", sep="", header=TRUE)
# assign factors
oedoplot$Block <- as.factor(oedoplot$Block)
oedoplot$Plot <- as.factor(oedoplot$Plot)
summary(oedoplot)

# Multi-stratum ANOVA (one-way ANOVA with blocks and psuedo-replication)
oedoplot.msaov <- aov(PlotCount ~ Treatment + Error(Block/Plot), data=oedoplot)
summary(oedoplot.msaov)

# Equivalent single-stratum ANOVA to get residuals
oedoplot.aov <- aov(PlotCount ~ Block + Treatment, data=oedoplot)
summary(oedoplot.aov)

# Residual plots
plot(oedoplot.aov, ask=FALSE)
hist(residuals(oedoplot.aov))

# Treatment means
model.tables(oedoplot.aov, type="means", se=TRUE)


### Trap-level counts

# Read data from file in working directory
oedotrap <- read.table("oedotrap.dat", sep="", header=TRUE)
# assign factors
oedotrap$Block <- as.factor(oedotrap$Block)
oedotrap$Plot <- as.factor(oedotrap$Plot)
oedotrap$Trap <- as.factor(oedotrap$Trap)
summary(oedotrap)

# Multi-stratum ANOVA (one-way ANOVA with blocks and psuedo-replication)
oedotrap.msaov <- aov(TrapCount ~ Treatment + Error(Block/Plot/Trap), data=oedotrap)
summary(oedotrap.msaov)

# Equivalent single-stratum ANOVA to get residuals
oedotrap.aov <- aov(TrapCount ~ Block + Treatment + Block:Plot, data=oedotrap)
summary(oedotrap.aov)

# Residual plots
plot(oedotrap.aov, ask=FALSE)
hist(residuals(oedotrap.aov))


# End of file