# Sensitivity Analysis of the effect of vaccine on viral load, # as described in Gilbert, Bosch, and Hudgens (2003, Biometrics). # This code gives an example of how to call the program in the # file Viral.Load.Sensitivity.Analysis.Program.r for producing # a sensitivity analysis. # Input parameters: # Set b (the number of bootstrap replications) >= 1000 b <- 1000 # Set the numbers randomized to vaccine and placebo: Nn1 <- 500 Nn0 <- 500 # Example simulated data-set- 50 infections in the vaccine group and 75 in the placebo group exampy1.samp <- rnorm(50,mean=4.0,sd=sqrt(.91)) exampy0.samp <- rnorm(75,mean=4.5,sd=sqrt(.75)) alpha1 <- .05 # Run the program repeatedly for beta varying between -5 and 5 (for example): source('Viral.Load.Sensitivity.Analysis.Program.r') for (i in seq(-5,5,length=51)) { beta <- i cat(paste("beta=",beta),"\n") viralloadprogram(b,Nn1,Nn0,exampy1.samp,exampy0.samp,alpha1,beta) } # The output can be found in the file output.dat in the same directory as the program was run # Plot the output using the code in the file Viral.Load.plots.r source('Viral.Load.plots.r') Viral.Load.plots("output.dat","figure1.ps","figure2.ps") # The plots of the results are in the same directory as the program was run # in the files figure1.ps and figure2.ps