estimateAUCwithFullCML: estimate AUC with Full censored maximum likelihood
In BLOQ: Impute and Analyze Data with BLOQ Observations

Description Usage Arguments Value Author(s) See Also Examples

function to estimate mean and and covariance matrix of censored data using a full censored maximum likelihood approach (with a special structure for the covariance matrix which only allows correlations between successive time points), then use these estimates for estimating AUC and its standard error

estimateAUCwithFullCML(
  inputData,
  LOQ,
  timePoints,
  isMultiplicative = FALSE,
  onlyFitCML = FALSE,
  printCMLmessage = TRUE,
  optimizationMethod = NULL,
  CMLcontrol = NULL,
  na.rm = TRUE
)

`inputData`	numeric matrix or data frame of the size n by J (n the sample size and J the number of time points) the input dataset
`LOQ`	scalar, limit of quantification value
`timePoints`	vector of time points
`isMultiplicative`	logical variable indicating whether an additive error model (FALSE) or a multiplicative error model (TRUE) should be used
`onlyFitCML`	logical variable with FALSE as default, if TRUE only the censored maximum likelihood estimates will be calculated
`printCMLmessage`	logical variable with TRUE as default, if TRUE then messages regarding the convergence status of censored log-likelihood maximization will be printed.
`optimizationMethod`	single string specifying the method to be used for optimizing the log-likelihood, the default is NULL that allows the function to decide the about the best method. Otherwise, one can select among choices available via R package maxLik: "NR" (for Newton-Raphson), "BFGS" (for Broyden-Fletcher-Goldfarb-Shanno), "BFGSR" (for the BFGS algorithm implemented in R), "BHHH" (for Berndt-Hall-Hall-Hausman), "SANN" (for Simulated ANNealing), "CG" (for Conjugate Gradients), or "NM" (for Nelder-Mead). Lower-case letters (such as "nr" for Newton-Raphson) are allowed.
`CMLcontrol`	list of arguments to control convergence of maximization algorithm. It is the same argument as control in the function maxLik in the R package maxLik
`na.rm`	logical variable indicating whether the lines with missing values should be ignored (TRUE, default) or not (FALSE).

a list with three components: output of maxLik function, estimated parameters (mean vector and the covariance matrix) using censored maximum likelihood, and estimated AUC and its standard error.

Vahid Nassiri, Helen Yvette Barnett

maxLik

#' # generate data from Beal model with only fixed effects
set.seed(123)
genDataFixedEffects <- simulateBealModelFixedEffects(10, 0.693,
	1, 1, seq(0.5,3,1.5))
estimateAUCwithFullCML(genDataFixedEffects, 0.15, seq(0.5,3,1.5))