Create a vectorized RSA model

This function integrates a vector_rsa_design and an mvpa_dataset to create a vectorized RSA model.

Usage

vector_rsa_model(
  dataset,
  design,
  distfun = cordist(),
  rsa_simfun = c("pearson", "spearman"),
  nperm = 0,
  save_distributions = FALSE,
  return_predictions = FALSE
)

Arguments

dataset

An mvpa_dataset object.

design

A vector_rsa_design object.

distfun

A distfun (distance function) for computing pairwise dissimilarities among image rows.

rsa_simfun

A character string specifying the similarity function to use for RSA, one of "pearson" or "spearman".

nperm

Integer, number of permutations for statistical testing (default: 0).

save_distributions

Logical, whether to save full permutation distributions (default: FALSE).

return_predictions

Logical, whether to return per-observation similarity scores (default: FALSE).

Value

A vector_rsa_model object (S3 class) containing references to the dataset, design, and function parameters.

Details

If `return_predictions` is TRUE, the output of `run_regional` or `run_searchlight` will include a `prediction_table` tibble containing the observation-level RSA scores.