psifr.stats.rank_lags#

psifr.stats.rank_lags(pool_items, recall_items, pool_label=None, recall_label=None, pool_test=None, recall_test=None, test=None)#

Calculate rank of absolute lag for free recall lists.

Parameters:

  • pool_items (list) – List of the serial positions available for recall in each list. Must match the serial position codes used in recall_items.

  • recall_items (list) – List indicating the serial position of each recall in output order (NaN for intrusions).

  • pool_label (list, optional) – List of the positions to use for calculating lag. Default is to use pool_items.

  • recall_label (list, optional) – List of position labels in recall order. Default is to use recall_items.

  • pool_test (list, optional) – List of some test value for each item in the pool.

  • recall_test (list, optional) – List of some test value for each recall attempt by output position.

  • test (callable) – Callable that evaluates each transition between items n and n+1. Must take test values for items n and n+1 and return True if a given transition should be included.

Returns:

rank – Absolute lag percentile rank for each included transition. The rank is 0 if the lag was the most distant of the available transitions, and 1 if the lag was the closest. Ties are assigned to the average percentile rank.

Return type:

list

See also

count_lags

Count actual and possible serial position lags.

Examples

>>> from psifr import stats
>>> pool_items = [[1, 2, 3, 4]]
>>> recall_items = [[4, 2, 3, 1]]
>>> stats.rank_lags(pool_items, recall_items)
[0.5, 0.5, nan]