AUCest.Rosner: Calculate AUC.c for measurement error based on probit-shift...
In correctedAUC: Correcting AUC for Measurement Error

Description Usage Arguments Value Author(s) References Examples

Calculate AUC.c for measurement error based on probit-shift model.

AUCest.Rosner(
  datFrame, 
  sidVar = "subjID", 
  obsVar = "y", 
  grpVar = "grp", 
  repVar = "myrep", 
  alpha = 0.05)

`datFrame`	a data frame with at least the following columns: `y`: numerical vector of observations; `subjID`: vector of subject ids; `grp`: group indicator: 1 means case; and 0 means conrol; `myrep`: integer vector indicating replication. should be consecutive positive integer starting from 1.
`sidVar`	character. variable name for subject id in the data frame `datFrame`.
`obsVar`	character. variable name for observations in the data frame `datFrame`.
`grpVar`	character. variable name for group indictor in the data frame `datFrame`.
`repVar`	character. variable name for replication indictor in the data frame `datFrame`.
`alpha`	confidence interval level 100(1-α%

A list of 9 elements:

`AUC.obs`	AUC estimated based on the Mann-Whitney statistic.
`AUC.c`	AUC corrected for measurement error based on the probit-shift model.
`ICC.x`	intra-class correlation for cases.
`ICC.y`	intra-class correlation for controls
`mu.mle`	maximum likelihood estimate of μ (i.e., the shift between the case distribution and the control distribution after probit transformation)
`AUC.obs.low`	lower bound of the `AUC.obs`.
`AUC.obs.upp`	upper bound of the `AUC.obs`.
`AUC.c.low`	lower bound of the `AUC.c`.
`AUC.c.upp`	upper bound of the `AUC.c`.

Bernard Rosner <stbar@channing.harvard.edu>, Shelley Tworoger <nhsst@channing.harvard.edu>, Weiliang Qiu <stwxq@channing.harvard.edu>

Rosner B, Tworoger S, Qiu W (2015) Correcting AUC for Measurement Error. J Biom Biostat 6:270. doi:10.4172/2155-6180.1000270

  set.seed(1234567)
  tt=genSimDataModelIII(
    nX = 100, 
    nY = 100, 
    mu = 0.25,
    lambda = 0,
    sigma.X2 = 1, 
    sigma.Y2 = 1, 
    sigma.e.X = 1, 
    sigma.e.Y = 1) 

  print(dim(tt$datFrame))
  print(tt$datFrame[1:2,1:3])
  print(tt$AUC.true)

  res = AUCest.Rosner(
    datFrame = tt$datFrame, 
    sidVar = "subjID",
    obsVar = "y",
    grpVar = "grp",
    repVar = "myrep",
    alpha = 0.05)
  print(res)