Free recall analysis

Managing data

table_from_lists(subjects, study, recall[, ...])	Create table format data from list format data.
check_data(df)	Run checks on free recall data.
merge_free_recall(data, **kwargs)	Score free recall data by matching up study and recall events.
merge_lists(study, recall[, merge_keys, ...])	Merge study and recall events together for each list.
filter_data(data[, subjects, lists, ...])	Filter data to get a subset of trials.
reset_list(df)	Reset list index in a DataFrame.
split_lists(frame, phase[, keys, names, ...])	Convert free recall data from one phase to split format.
pool_index(trial_items, pool_items_list)	Get the index of each item in the full pool.
block_index(list_labels)	Get index of each block in a list.

Recall probability

spc(df)	Serial position curve.
pnr(df[, item_query, test_key, test])	Probability of recall by serial position and output position.

Intrusions

pli_list_lag(df, max_lag)

List lag of prior-list intrusions.

Transition probability

lag_crp(df[, lag_key, count_unique, ...])	Lag-CRP for multiple subjects.
category_crp(df, category_key[, item_query, ...])	Conditional response probability of within-category transitions.
distance_crp(df, index_key, distances, edges)	Conditional response probability by distance bin.

Transition rank

lag_rank(df[, item_query, test_key, test])	Calculate rank of the absolute lags in free recall lists.
distance_rank(df, index_key, distances[, ...])	Calculate rank of transition distances in free recall lists.

Plotting

plot_raster(df[, hue, palette, marker, ...])	Plot recalls in a raster plot.
plot_spc(recall, **facet_kws)	Plot a serial position curve.
plot_lag_crp(recall[, max_lag, split])	Plot conditional response probability by lag.
plot_distance_crp(crp[, min_samples])	Plot response probability by distance bin.
plot_swarm_error(data[, x, y, swarm_color, ...])	Plot points as a swarm plus mean with error bars.

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psifr.fr.table_from_lists