R/Bootstrap_functions.r
bootstrapSamples_limRots_block.RdThis function generates stratified bootstrap samples identical to
bootstrapSamples_limRots, but additionally supports correlation
blocks. When correlation_block is specified, all samples sharing
the same block ID are always selected together during resampling.
When correlation_block is NULL, the function delegates entirely
to bootstrapSamples_limRots.
bootstrapSamples_limRots_block(
niter,
meta.info,
group,
correlation_block = NULL
)Integer. The number of bootstrap samples to generate.
Data frame. Metadata containing sample information,
where each row corresponds to a sample. Factor columns in meta.info
are used to define strata for sampling.
Character. The name of the column in meta.info that
defines the grouping variable for the samples.
Character or NULL. The name of a column in
meta.info that defines correlation blocks. Samples sharing the same
value in this column are always resampled together as a unit. If NULL,
the function behaves identically to bootstrapSamples_limRots.
A matrix of dimension niter x n, where n is the
number of samples. Each row corresponds to a bootstrap sample, and each
entry is a resampled row name from the metadata, stratified by group and
additional factors.
The function follows the same logic as bootstrapSamples_limRots:
within each group defined by group, it identifies factor
columns to create strata, then samples proportionally within each stratum.
When correlation_block is not NULL, entire blocks (e.g., repeated
measures from the same subject) are resampled together as a unit instead
of individual samples.