Compares first-order encoding-retrieval transfer with second-order geometry preservation using matched variance-partition models. The model builds item-level prototypes in a source state (`dataset$train_data`) and a target state (`dataset$test_data`), then estimates how much variance is uniquely explained by same-item transfer and by source-state geometry after optional nuisance pair models.
Usage
era_partition_model(
dataset,
design,
key_var,
distfun = cordist(method = "pearson"),
rsa_simfun = c("pearson", "spearman"),
first_order_nuisance = NULL,
second_order_nuisance = NULL,
item_block_enc = NULL,
item_block_ret = NULL,
item_time_enc = NULL,
item_time_ret = NULL,
item_category = NULL,
include_procrustes = TRUE,
procrustes_center = TRUE,
min_procrustes_train_items = 3L,
return_matrices = FALSE,
...
)Arguments
- dataset
An `mvpa_dataset` with `train_data` and `test_data`.
- design
An `mvpa_design` with train/test design tables.
- key_var
Column name or formula giving the item key shared across source and target states.
- distfun
Distance function used for within-state RDMs.
- rsa_simfun
Correlation method for the raw geometry summary.
- first_order_nuisance
Optional named list of `K x K` matrices or length `K^2` vectors for cross-state similarity nuisance regressors. Matrices are interpreted as target rows by source columns.
- second_order_nuisance
Optional named list of `K x K` matrices or lower-triangle vectors for geometry nuisance regressors.
- item_block_enc, item_block_ret
Optional item-level block labels for source and target states. Named vectors are matched to item keys.
- item_time_enc, item_time_ret
Optional item-level time/order values for source and target states. Named vectors are matched to item keys.
- item_category
Optional item-level category labels used to add a same-category nuisance model to both first- and second-order regressions.
- include_procrustes
Logical; compute leave-one-item-out orthogonal Procrustes cross-decoding metrics.
- procrustes_center
Logical; center source and target prototypes using only alignment-training items before fitting Procrustes maps.
- min_procrustes_train_items
Minimum number of paired items allowed for each leave-one-item-out Procrustes alignment.
- return_matrices
Logical; store prototype/similarity matrices in each ROI result for diagnostics.
- ...
Additional fields stored on the model spec.