9.5 Data preparation for R2WinBUGS

First we need to load the packages needed for the exercise
library(R2WinBUGS)
library(sp)
library(spdep)
library(rgdal)

Now open the script "SnowyR2winbugs.R" and run code directly from the script

df <- read.table("SnowyFinal.txt", sep="\t")
head(df)
str(df)
df$IDvar <- substr(df$id, 2,5)
df$IDvar <- as.integer(df$IDvar)
#Clean up and remove missing data for disease status, sex, and age
summary(df$Status)
df <- subset(df, df$Status !="Unknown")
df$Status <- factor(df$Status)
summary(df$Status)
#Recode Sex classes and remove NAs
summary(df$Sex)
df <- subset(df, df$Sex !="")
df$Sex <- factor(df$Sex)
df$Sex2 <- as.character(df$Sex)
df$Sex2[df$Sex2 == "Male"] <- "1"
df$Sex2[df$Sex2 == "Female"] <- "0"
df$Sex2
#Recode Age classes and remove NAs
summary(df$Age)
df <- subset(df, df$Age !="")
df$Age <- factor(df$Age)
table(df$Age)
#Age classes
# 2-5 3 6+ Adult Calf Yearling
# 188 1 79 5 36 30
#Combine ages classes
df$NewAge <- df$Age
levels(df$NewAge)<-list(Yearling=c("Calf","Yearling"),Adult=c("2-5","3","6+","Adult"))
summary(df$NewAge)
#Now convert age to numeric with Yearling=0 (baseline) and Adult=1
df$Age2 <- df$NewAge
df$Age2 <- as.character(df$Age2)
df$Age2[df$Age2 == "Adult"] <- "1"
df$Age2[df$Age2 == "Yearling"] <- "0"
df$Age2
df$KillYear <- as.factor(df$KillYear)

summary(df$KillYear)
#2009 2011 2012
23 15 1

#NOTE: We added 3 cells around outer most samples to encompass all disease
#samples until can figure out how to expand grid polygons
snowy.df <- as.data.frame(df.spdf)
str(snowy.df)
minx <- (min(snowy.df$x)-10830)
maxx <- (max(snowy.df$x)+10830)
miny <- (min(snowy.df$y)-10830)
maxy <- (max(snowy.df$y)+10830)