Impute and Analyze Data with BLOQ Observations

Documentation for package ‘BLOQ’ version 0.1-1

estimateAUCandStdErr	Estimate AUC and its standard error
estimateAUCwithCMLperTimePoint	estimate AUC with censored maximum likelihood per time point
estimateAUCwithFullCML	estimate AUC with Full censored maximum likelihood
estimateAUCwithMVNCML	estimate AUC with multivariate normal censored maximum likelihood
estimateAUCwithPairwiseCML	estimate AUCwith pairwise censored maximum likelihood
imputeBLOQ	impute BLOQ's with various methods
imputeCML	imputing BLOQ's using censored maximum likelihood
imputeConstant	imputing BLOQ's with a constant value
imputeKernelDensityEstimation	imputing BLOQ's using kernel density estimation
imputeROS	imputing BLOQ's using regression on order statistics
simulateBealModelFixedEffects	simulate data from Beal model with fixed effects
simulateBealModelMixedEffects	simulate data from Beal model with fixed and random effects