modelOutcome: Compare regression coefficients across studies
In MergeMaid: Merge Maid

Description Usage Arguments Value See Also Examples

Given a set of merged studies, this function calculates study specific regression coefficients for each gene.

1	modelOutcome(x,outcome,outcome2=NULL,method=c("linear","logistic","cox"),...)

`x`	Object of class mergeExpressionSet.
`method`	Method specifies the model used to generate coefficients. At this time only linear regression, logistic regression, and Cox hazard rates are implemented.
`outcome, outcome2`	The format for the outcome variable depends on the model used. For linear regression, outcome should be a continous response variable, for logistic regression, it should be a binary response variable, and for Cox hazard rates it should be time of event. Outcome 2 is currently used only in the calculation of hazard rates, and should be a binary variable indicating censoring status for each subject. If outcome is a vector of length equal to number of studies, then each element represents the column in the ExpressionSet phenoData slot for that study. If outcome is a list, then each list element should have actual outcome data for the corresponding study.
`...`	Not implemented at this time

The output is a mergeCoeff object.

modelOutcome, mergeCoeff-class

  if(require(Biobase) & require(MASS) & require(survival)){
  data(mergeData)
  merged  <- mergeExprs(sample1,sample2,sample3)

  log.coeff  <- modelOutcome(merged,outcome=c(1,1,1),method="logistic")
  plot(coeff(log.coeff))
  
  linear.coeff  <- modelOutcome(merged[1:2],outcome=c(3,3),method="linear")
  plot(zscore(linear.coeff),xlab="study 1",ylab="study 2")

  event1<-rbinom(100,1,.5)
  event2<-rbinom(50,1,.5) 
  event3<-rbinom(70,1,.5)

  out1<-rnorm(100,5,1)
  out2<-rnorm(50,5,1)
  out3<-rnorm(70,5,1)

  out<-list(out1,out2,out3)
  even<-list(event1,event2,event3)

  cox.coeff<-modelOutcome(merged,outcome2=even,outcome=out,method="cox")
  plot(coeff(cox.coeff))

  }