#clean the environment
rm(list=ls())

#make sure the working directory is correct
getwd()
setwd("C:/Users/aamahama/Desktop/")

#make sure you have not exceeded the number of lines that you can print
getOption("max.print")
options(max.print=1000000)

#install the package for linear mixed equations
install.packages("lme4")

#load the lme4 package for use
library(lme4)


#Next load in the data set from a spreadsheet (excel.csv)
ds2<-read.csv("ds 2.csv",header=T)


#designate some variables as factor variables
attach(ds2)
ds2$env<-factor(ds2$env)
ds2$line<-factor(ds2$line)
ds2$blk<-factor(ds2$blk)
summary(ds2)
detach(ds2)


# Compare with type III MM
attach(ds2)
anova(lm(yld~ env +line + mat + env*line))
#could also calculate the lsmeans for comparisons with predicted values.insert lsmeans code here.

#output to a file
sink("anova of ds2.txt")
anova(lm(yld~env+line+mat+env*line))
sink()

#designate the mixed linear model for the data
ds2.mixmodel = lmer(yld ~ env+mat+(1|line/env))

ds2.mixmodel
#output random effects from DS4.
ranef(ds2.mixmodel)