MI_cv_naive function

Naive method for Cross-validation in Multiply Imputed datasets

MI_cv_naive Cross-validation by applying multiply imputed pooled models in train and test folds. Called by function psfmi_perform.

MI_cv_naive(pobj, folds = 3, p.crit = 1, BW = FALSE, cv_naive_appt = TRUE)

Arguments

• pobj: An object of class pmods (pooled models), produced by a previous call to psfmi_lr.
• folds: The number of folds, default is 3.
• p.crit: A numerical scalar. P-value selection criterium used for backward during cross-validation. When set at 1, pooling and internal validation is done without backward selection.
• BW: If TRUE backward selection is conducted within cross-validation. Default is FALSE.
• cv_naive_appt: Default is TRUE for showing the cross-validation apparent (train) and test results. Set to FALSE to only give test results.

See Also

psfmi_perform

Author(s)

Martijn Heymans, 2020