# First load and view the dataset
dat.tf <- read.csv("Banta_TotalFruits.csv")
str(dat.tf)

# X  observation number 
# reg  factor for one of three regions; Netherlands, Spain or Sweden
# popu  factor with a level for each population (random effect)
# gen  factor with a level for each genotype (random effect)
# rack  nuisance factor for one of two greenhouse racks
# nutrient  factor with levels for low (value = 1) or high (value = 8) nutrients (fixed effect)
# amd  factor with levels for no damage or simulated herbivory (apical meristem damage) (fixed effect)
# status  nuisance factor for germination method
# total.fruits  the response variable; an integer indicating the number of fruits per plant 

# 2-3 genotypes nested within each of the 9 populations
table(dat.tf$popu,dat.tf$gen)

# Housekeeping: make integers into factors, relevel clipping (amd) and rename nutrient levels
dat.tf <- transform(dat.tf,
                    X=factor(X),
                    gen=factor(gen),
                    rack=factor(rack),
                    amd=factor(amd,levels=c("unclipped","clipped")),
                    nutrient=factor(nutrient,label=c("Low","High")))

# Install/load packages
if(!require(lme4)){install.packages("lme4")}
require(lme4)
if(!require(coefplot2)){install.packages("coefplot2",repos="http://www.math.mcmaster.ca/bolker/R",type="source")}
require(coefplot2)     
if(!require(reshape)){install.packages("reshape")}
require(reshape) 
if(!require(ggplot2)){install.packages("ggplot2")}
require(ggplot2)
if(!require(plyr)){install.packages("plyr")}
require(plyr)
if(!require(gridExtra)){install.packages("gridExtra")}
require(gridExtra)
if(!require(emdbook)){install.packages("emdbook")}
require(emdbook)
source("glmm_funs.R")