Produce several disjoint matched item sets (items as a random factor)

Each replicate is an independent, fully matched set drawn from the pool with the items of earlier replicates removed, so no item is reused. This lets a study treat its items as a random factor (running different item samples across participant groups, or showing an effect holds across samples) instead of treating them as a fixed set (Clark, 1973; Yarkoni, 2022). Deterministic and identical to the Python engine.

Usage

resample_stimuli(pool, design, schema, n_sets, verbose = FALSE)

Arguments

pool

A candidate pool with the match_on dimensions present.

design

A parsed design configuration.

schema

The parsed global schema.

n_sets

Number of disjoint matched sets to draw, a whole number of at least 1.

verbose

Logical; passed to match_stimuli().

Value

A data frame of matched stimuli with an added replicate column. The first replicate draws on the whole pool, so its count of the candidates excluded for a missing matched value is the one recorded in the "audit" attribute's incomplete_dropped entry, as match_stimuli() records it. A relaxed tolerance window inside a replicate is not recorded: it reaches the console under verbose but not the run log or the datasheet.