psifr.fr.pli_list_lag#

psifr.fr.pli_list_lag(df, max_lag)#

List lag of prior-list intrusions.

Parameters:

  • df (pandas.DataFrame) – Merged study and recall data. See merge_free_recall. Must have fields: subject, list, intrusion, prior_list. Lists must be numbered starting from 1 and all lists must be included.

  • max_lag (int) – Maximum list lag to consider. The intial max_lag lists for each subject will be excluded so that all considered lags are possible for all included lists.

Returns:

results – For each subject and list lag, the proportion of intrusions at that lag, in the results['prob'] column.

Return type:

pandas.DataFrame

Examples

>>> from psifr import fr
>>> raw = fr.sample_data('Morton2013')
>>> data = fr.merge_free_recall(raw)
>>> fr.pli_list_lag(data, 3)
     subject  list_lag  count  per_list      prob
0          1         1      7  0.155556  0.259259
1          1         2      5  0.111111  0.185185
2          1         3      0  0.000000  0.000000
3          2         1      9  0.200000  0.191489
4          2         2      2  0.044444  0.042553
..       ...       ...    ...       ...       ...
115       46         2      1  0.022222  0.100000
116       46         3      0  0.000000  0.000000
117       47         1      5  0.111111  0.277778
118       47         2      1  0.022222  0.055556
119       47         3      0  0.000000  0.000000

[120 rows x 5 columns]