BLOQ (version 0.1-1)

estimateAUCandStdErr: Estimate AUC and its standard error

Description

function to estimate AUC and compute standard error of this estimate

Usage

estimateAUCandStdErr(
  imputedData,
  timePoints,
  isMultiplicative = FALSE,
  na.rm = FALSE
)

Arguments

imputedData

numeric matrix or data frame of size n by J (n the sample size and J the number of time points)

timePoints

vector of time points

isMultiplicative

logical variable indicating whether an additive error model (FALSE) or a multiplicative error model (TRUE) should be used

na.rm

logical variable indicating whether the rows with missing values should be ignored or not.

Value

vector of length 2 with estimated AUC and its standard error

Examples

# NOT RUN {
# generate data from Beal model with only fixed effects
set.seed(111)
genDataFixedEffects <- simulateBealModelFixedEffects(10, 0.693,
+ 		1, 1, seq(0.5,3,0.5))
# Impute the data with BLOQ's with one of the provided methods,
# for example, here we use ROS
imputedDataROS <- imputeROS(genDataFixedEffects, 0.1)
# estimate AUC and its standard error
estimateAUCandStdErr(imputedDataROS,seq(0.5,3,0.5))

# }