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

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)
#> Summary of prepared data (values for supplied data in paretheses)
#> - Number of respondents: 881 (888)
#> - Number of stimuli: 6 (6)
#> - Number of stimuli obs.: 4937 (4973)
#> - Range of observations: [-3, 3] ([1, 7])

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