plotVElatCont {CoRpower} | R Documentation |
Plotting Treatment (Vaccine) Efficacy Curves for Different Correlate of Risk Relative Risks for Continuous Biomarkers
Description
Plots the treatment (vaccine) efficacy curve for the true latent biomarker for eight different values of the latent correlate of risk
relative risk and the lowest vaccine efficacy level for the true biomarker. All curves assume rho=1
, and treatment (vaccine)
efficacy ranges from 0 to 1. The legend is completely determined by the function.
Usage
plotVElatCont(outComputePower, outDir = NULL)
Arguments
outComputePower |
a list of lists of length |
outDir |
a character string specifying path to output |
Details
computePower
function input parameter VElowest
must have length greater than or equal to eight
for all eight scenarios to have unique RRc and VElowest. Otherwise, only length(VElowest)
unique
VE curves will be displayed.
When interpreting the output of the function, the null hypothesis corresponds to a flat curve where vaccine efficacy for all values of the
true latent biomarker is equal to the overall vaccine efficacy. Increasing departures from the null hypothesis correspond
to increasingly variable and steep VE curves. The output assumes the overall placebo-group endpoint risk between \tau
and \tau_{max}
is constant for all values of the latent and observed biomarker and that there is no measurement error (\rho=1
). When this is the case,
an association of the biomarker with infection risk in the vaccine group (a correlate of risk) is equivalent to an association of the biomarker
with treatment (vaccine) efficacy.
The function's plot can also be interpreted in conjunction with the output of the plotPowerCont
function by
matching the CoR relative risk in the two plots and examining power compared to VE. This sheds light on the importance
of overall VE on power and further enables correlates of risk results to be interpreted in terms of
potential correlates of efficacy/protection.
Value
None. The function is called solely for plot generation.
See Also
Examples
# Example scenario with continuous biomarker, where values of rho are varied
# Set input parameters for computePower function
nCasesTx <- 10
nControlsTx <- 300
nCasesTxWithS <- 10
controlCaseRatio <- 3
VEoverall <- 0.75
risk0 <- 0.034
PlatVElowest <- 0.2
VElowest <- seq(0, VEoverall, len=8)
Plat0 <- P0 <- 0.2
Plat2 <- P2 <- 0.6
M <- 13
alpha <- 0.05
sigma2obs <- 1
rho <- 1
biomType <- "continuous"
# Output from computePower function is stored in an object as a list
pwr <- computePower(nCasesTx=nCasesTx, nControlsTx=nControlsTx, nCasesTxWithS=nCasesTxWithS,
controlCaseRatio=controlCaseRatio, risk0=risk0, VEoverall=VEoverall,
PlatVElowest=PlatVElowest, VElowest=VElowest, Plat0=Plat0, Plat2=Plat2,
P0=P0, P2=P2, M=M, alpha=alpha, sigma2obs=sigma2obs, rho=rho, biomType=biomType)
# Set parameters for plotPowerCont function
# outComputePower is a list containing output from the computePower function
outComputePower <- pwr
plotVElatCont(outComputePower=outComputePower)
## Not run:
# Output from computePower function is saved in an RData file
computePower(..., saveDir = "myDir", saveFile = "myFile.RData")
# outComputePower is a character string specifying the file containing the computePower output
# outDir is a character string specifying the outComputePower file directory
outComputePower <- "myFile.RData"
outDir <- "~/myDir"
plotVElatCont(outComputePower, outDir=outDir)
## End(Not run)