#this R script performs proportional hazards regression to test for effects of propagule
#introduction frequency and number on extinction time in experimental Daphnia populations

#Details are provided in the following paper:
#Drake, J.M., P. Baggenstos, & D.M. Lodge. 2005. Propagule pressure and persistence in experimental populations. Biology Letters 1:480-483. doi:10.1098/rsbl.2005.0375

#this script requires the 'survival' package

library(survival)
data<-read.table('ext_time.csv',header=T,sep=",")
attach(data)
rate<-IntroNum*IntroFreq
surv.data<-Surv(time, censored)
hyp1<-coxph(surv.data~IntroNum+IntroFreq+rate,method='exact')
summary(hyp1)
hyp2<-coxph(surv.data~IntroNum+IntroFreq,method='exact')
summary(hyp2)
hyp3<-coxph(surv.data~rate,method='exact')
summary(hyp3)
hyp4<-coxph(surv.data~IntroNum+rate,method='exact')
summary(hyp4)
hyp5<-coxph(surv.data~IntroFreq+rate,method='exact')
summary(hyp5)

data2<-read.table('final_date.csv',header=T,sep=",")
attach(data2)
corr<-cor.test(Rate,extinct,method="kendall")
win.graph()
plot(Rate, extinct)
persist=1-extinct
persistence0<-glm(persist~rate+IntroFreq+IntroNum,family=binomial)
persistence1<-glm(persist~rate,family=binomial)
persistence2<-glm(persist~rate+IntroFreq,family=binomial)
persistence3<-glm(persist~rate+IntroNum,family=binomial)