##### Nested Designs - Split plot designs and other designs


### import data - data set 1 (splitplot)


datum=read.csv(file.choose())
head(datum)


###Analyze data: water plots nested within fertilizer plots, nested within cow plots, nested within fields


results=lme(Biomass~Cow+Fertilizer+Water,data=datum,random=~1|Field/Cow/Fertilizer)
# no need for 'water' in random effect, water plots are the residual errors (only measured once)
anova(results)
summary(results)
# Notice appropriate den degrees of freedom, accounting for nested samples (pseudoreplicates)


### import data - dataset 2 (Nested ANCOVA)


datum=read.csv(file.choose())
head(datum)


###Analyze data: block by individual, which is nested within sex


results=lme(Biomass~Age+Sex,data=datum,random=~1|Individual)
anova(results)
# notice appropriate den degree of freedom, accounting for nested samples (pseudoreplicated by sex)
summary(results)


### Analyze data with interaction (no interaction in data)


results=lme(Biomass~Age+Sex+Sex:Age,data=datum,random=~1|Individual)
anova(results)
summary(results)
# Note that sex:age is not pseudoreplicated; uses full error term