MI_boot: Bootstrap validation in Multiply Imputed datasets

In psfmi: Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets

Bootstrap validation in Multiply Imputed datasets

Description

MI_boot Bootstrapping in each (original) Multiply Imputed dataset for internal validation. Called by function psfmi_perform.

Usage

MI_boot(pobj, p.crit, nboot, direction)

Arguments

pobj	An object of class pmods (pooled models), produced by a previous call to psfmi_lr.
p.crit	A numerical scalar. P-value selection criterium used for backward or forward selection during in the bootstrap samples. When set at 1, validation is done without variable selection.
nboot	The number of bootstrap resamples, default is 10.
direction	The direction of predictor selection, "BW" is for backward selection and "FW" for forward selection.

Author(s)

Martijn Heymans, 2020

See Also

psfmi_perform

psfmi documentation built on July 9, 2023, 7:02 p.m.