AUCest.Rosner {correctedAUC}

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

Description

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

Usage

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

Arguments

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-\alpha%

Value

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 \mu (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.

Author(s)

Bernard Rosner <[e-mail]>, Shelley Tworoger <[e-mail]>, Weiliang Qiu <[e-mail]>

References

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

Examples

  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)