# R help to Exercise 20

 

# You may read the data into R by the command:

insects=read.table("http://www.uio.no/studier/emner/matnat/math/STK4900/data/insects.txt",header=T)

 

 

# Question a)

 

# Compute the proportion dead at the various doses and plot the proportions versus logdose:

 

proportion<-insects$DEAD/insects$NUMBER

plot(insects$LOGDOSE, proportion, ylim=c(0,1),pch=16)

 

# Try to make the plot look nice by giving appropriate labels for the x-axis and the y-axis.

 

 

# Question b)

 

# Fit a logistic regression model with logdose as covariate and look at the result:

# (Note that since we have grouped data, not binary, the response has to be specified as

# cbind(y,n-y) where n=number of individuals in a group and y=number of "successes" in the group.)

 

fit<-glm(cbind(DEAD,NUMBER-DEAD)~LOGDOSE, data=insects,family=binomial)

summary(fit)

 

 

# Question c)

 

# Compute the probabilities obtained from the fitted model and include them in the plot from question a

 

pred.prop=predict(fit,type="response")

points(insects$LOGDOSE ,pred.prop)

 

# We may also draw a curve that describes the fitted logistic model:

logdose=seq(0.4,1,0.01)

new.doses=data.frame(LOGDOSE=logdose)

lines(logdose,predict(fit,new.doses,type="response"))