sampleConditional: Complete a dataset conditional on a model and the outcomes
In EMLasso: Fit (logistic) LASSO when there is missing data in the predictors

Description Usage Arguments Value Author(s) See Also

Complete a dataset conditional on a model and the outcomes

  sampleConditional(predictorModel, outcomeModel,
    nrOfSamplesPerMDRow, ds, out, rowsToUseForFit,
    imputeDs2FitDsProperties, reusableForSampling,
    reusableForvalidation, verbosity = 0)

  ## S3 method for class 'GLoMo'
sampleConditional(predictorModel,
    outcomeModel, nrOfSamplesPerMDRow, ds, out,
    rowsToUseForFit, imputeDs2FitDsProperties,
    reusableForSampling, reusableForvalidation,
    verbosity=0)

  acceptOrRejectFunction(outcomeModel)

  ## Default S3 method:
acceptOrRejectFunction(outcomeModel)

  ## S3 method for class 'lognet'
acceptOrRejectFunction(outcomeModel)

`predictorModel`	model binding the predictors (e.g. `GLoMo`)
`outcomeModel`	outcome model (linking the outcomes to the predictors) (e.g. `glmnet` object)
`nrOfSamplesPerMDRow`	number times each row with missing data will be completed
`ds`	dataset to be completed
`out`	outcomes
`rowsToUseForFit`	which of the rows in `ds` can be used for fitting the outcome model
`imputeDs2FitDsProperties`	see `imputeDs2FitDs`
`reusableForSampling`	Which of the rows of dfr/out can be used for fitting the LASSO
`reusableForvalidation`	minimum number of iterations before convergence is possible
`verbosity`	The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output)

object of classes "sampledConditionallyGLomo" and "sampledConditionally", which is a list with items:

ds: completed dataset
out: outcome per row of ds (the one in this list)
weights: weight per row in ds (the one in this list)
orgri: row index within ds (the parameter of the function) of each row within ds (the one in this list)
useForFit: boolean indicator for each row of ds (the one in this list) that is TRUE if this row is to be used for validation
useOut: outcomes, but only for the rows of ds that can be used for validation