subset.metapred: Subsetting metapred fits

In metamisc: Meta-Analysis of Diagnosis and Prognosis Research Studies

Description

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

Usage

## 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.

Value

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.

Author(s)

Valentijn de Jong

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.

metamisc documentation built on Oct. 13, 2021, 3 p.m.