genSimDataModelIII: Generate one simulated data set based on Model III in Rosner...
In correctedAUC: Correcting AUC for Measurement Error

Description Usage Arguments Details Value Author(s) References Examples

Generate one simulated data set based on Model III in Rosner et al's (2015) manuscript.

genSimDataModelIII(
  nX, 
  nY, 
  mu,
  lambda,
  sigma.X2, 
  sigma.Y2, 
  sigma.e.X, 
  sigma.e.Y)

`nX`	integer. number of cases.
`nY`	integer. number of controls.
`mu`	difference of means between the case distribution and control distribution.
`lambda`	mean for controls.
`sigma.X2`	variance of the true value for cases.
`sigma.Y2`	variance of the true value for controls.
`sigma.e.X`	variance of the random error term for cases.
`sigma.e.Y`	variance of the random error term for controls.

The Model III in Rosner et al.'s (2005) manuscript:

X_{ik, obs}=X_{i,true}+ε_{ik}, log(X_{i, true}) ~ N(lambda+mu, sigma.X2), log(ε_{ik}) ~ N(0, sigma.epsilon2), i=1,…, nX, k=1, 2

Y_{jl, obs}=Y_{j,true}+ξ{jl}, log(Y_{j, true}) ~ N(lambda, sigma.Y2), log(ξ_{jl}) ~ N(0, sigma.eta2), j=1,…, nY, l=1, 2

A list of 2 elements:

`datFrame`	A data frame with 4 elements: `y`: observations; `subjID`: subject ID; `grp`: group indicator; `myrep`: replication indicator.
`AUC.true`	true AUC value

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)