prep_data_cv: Prepare data for a K-fold cross-validation of an HBAM model

In hbamr: Hierarchical Bayesian Aldrich-McKelvey Scaling via 'Stan'

Prepare data for a K-fold cross-validation of an HBAM model

Description

This function turns data prepared for hbam() into a list of K versions, where each version includes a different vector identifying holdout-data.

Usage

prep_data_cv(data, K = 10, seed = 1)

Arguments

data	A list of data produced by prep_data().
K	An integer above 2, specifying the number of folds to use in the analysis. Defaults to 10.
seed	An integer passed on to set.seed before creating the folds to increase reproducibility. Defaults to 1.

Value

A list of K data objects where each version includes a different vector identifying holdout-data.

Examples

# Loading and re-coding ANES 1980 data:
data(LC1980)
LC1980[LC1980 == 0 | LC1980 == 8 | LC1980 == 9] <- NA
self <- LC1980[, 1]
stimuli <- LC1980[, -1]
dat <- prep_data(self, stimuli)

# Prepare data for cross-validation:
dat_cv <- prep_data_cv(dat, K = 10)

hbamr documentation built on April 4, 2025, 3:06 a.m.