View source: R/densitycontrol.aroc.R
densitycontrol.aroc | R Documentation |
This function is used to set various parameters controlling the estimation of the conditional densities of test outcomes in the healthy group.
densitycontrol.aroc(compute = FALSE, grid.h = NA, newdata = NA)
compute |
Logical value. If TRUE the conditional densities of test outcomes in the healthy group are estimated. |
grid.h |
Grid of test outcomes in the healthy group where the conditional density estimates are to be evaluated. Value |
newdata |
Data frame containing the values of the covariates at which the conditional density estimates are computed. |
The value returned by this function is used as a control argument of the AROC.bnp
function.
A list with components for each of the possible arguments.
AROC.bnp
library(ROCnReg)
data(psa)
# Select the last measurement
newpsa <- psa[!duplicated(psa$id, fromLast = TRUE),]
# Log-transform the biomarker
newpsa$l_marker1 <- log(newpsa$marker1)
# Covariate for prediction
agep <- seq(min(newpsa$age), max(newpsa$age), length = 5)
df.pred <- data.frame(age = agep)
AROC_bnp <- AROC.bnp(formula.h = l_marker1 ~ f(age, K = 0),
group = "status",
tag.h = 0,
data = newpsa,
standardise = TRUE,
p = seq(0, 1, len = 101),
compute.lpml = TRUE,
compute.WAIC = TRUE,
compute.DIC = TRUE,
pauc = pauccontrol(compute = TRUE, value = 0.5, focus = "FPF"),
density = densitycontrol.aroc(compute = TRUE, grid.h = NA, newdata = df.pred),
mcmc = mcmccontrol(nsave = 500, nburn = 100, nskip = 1)
)
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