#Load and assign data
data.Fram<-as.matrix(read.table(file="Framinghamdata.txt"))
W1       <-data.Fram[,1]
W        <- W1
W2       <-data.Fram[,2]
Z        <-data.Fram[,3]
chd      <-data.Fram[,4]

# Compute the measurement error variance
sigmasqu <- var(W1-W2) / 2

# Run the naive logistic regression
naive.model <- glm(chd ~ Z + W, family = binomial(link="logit"), x=TRUE)

# Run SIMEX with B = 100 replicates. Use the quadratic extrapolantRsimex

simex.model <- simex(model = naive.model, SIMEXvariable = "W", measurement.error = sqrt(sigmasqu), lambda = c(0.5,1.0,1.5,2.0), B=100,
                       fitting.method = "quad")

# Plot the SIMEX trace plot
plot(simex.model,mfrow = c(2,2))

# Give the SIMEX values for all lambda
simex.model$SIMEX.estimates

# Give the jackknife variance estimates
simex.model$variance.jackknife

# Give the results of the naive model
simex.model$model