subset.metapred function

Subsetting metapred fits

Return a model from the cross-validation procedure or the final 'global' model. Caution: This function is still under development.

## S3 method for class 'metapred'
subset(
  x,
  select = "cv",
  step = NULL,
  model = NULL,
  stratum = NULL,
  add = TRUE,
  ...
)

Arguments

• x: metapred object
• select: Which type of model to select: "cv" (default), "global", or (experimental) "stratified", or "stratum".
• step: Which step should be selected? Defaults to the best step. numeric is converted to name of the step: 0 for an unchanged model, 1 for the first change...
• model: Which model change should be selected? NULL (default, best change) or character name of variable or (integer) index of model change.
• stratum: Experimental. Stratum to return if select = "stratum".
• add: Logical. Add data, options and functions to the resulting object? Defaults to TRUE. Experimental.
• ...: For compatibility only.

Returns

An object of class mp.cv for select = "cv" and an object of class mp.global for select = "global". In both cases, additional data is added to the resulting object, thereby making it suitable for further methods.

Examples

data(DVTipd)
DVTipd$cluster <- letters[1:4] # Add a fictional clustering to the data.
mp <- metapred(DVTipd, strata = "cluster", formula = dvt ~ histdvt + ddimdich, family = binomial)
subset(mp) # best cross-validated model
subset(mp, select = "global") # Final model fitted on all strata.
subset(mp, step = 1) # The best model of step 1
subset(mp, step = 1, model = "histdvt") # The model in which histdvt was removed, in step 1.

Author(s)

Valentijn de Jong