genSimDataReiser: Generate one simulated data set based on Reiser's (2000)...
In correctedAUC: Correcting AUC for Measurement Error

Description Usage Arguments Details Value Author(s) References Examples

Generate one simulated data set based on Reiser's (2000) model. The true AUC will also be calculated.

genSimDataReiser(
  nX = 100, 
  nY = 100, 
  sigma.X2 = 1, 
  mu.X = 0.25, 
  sigma.Y2 = 1, 
  mu.Y = 0, 
  sigma.epsilon2 = 0.5, 
  sigma.eta2 = 0.5)

`nX`	integer. number of cases.
`nY`	integer. number of controls.
`sigma.X2`	variance of the true value for cases.
`mu.X`	mean of the true value for cases.
`sigma.Y2`	variance of the true value for controls.
`mu.Y`	mean of the true value for controls.
`sigma.epsilon2`	variance of the random error term for cases.
`sigma.eta2`	variance of the random error term for controls.

Reiser's (2000) measurement error model is:

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

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

A list of 4 elements:

`datFrame`	A data frame with 4 elements: `y`: observations; `subjID`: subject ID; `grp`: group indicator; `myrep`: replication indicator.
`theta2`	(sigma.epsilon2 + sigma.eta2)/(sigma.X2 + sigma.Y2)
`mu.true`	mu.X-mu.Y
`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=genSimDataReiser(
       nX = 100, 
       nY = 100, 
       sigma.X2 = 1, 
       mu.X = 0.25, 
       sigma.Y2 = 1, 
       mu.Y = 0, 
       sigma.epsilon2 = 0.5, 
       sigma.eta2 = 0.5) 

  print(dim(tt$datFrame))
  print(tt$datFrame[1:2,1:3])
  print(tt$theta2)
  print(tt$mu.true)
  print(tt$AUC.true)