FAM_FACTOR
Define a familiarity factor to distinguish between new and old test items.
Contents
Basic familiarity factor
FAM_FACTOR(aglss, 'fname') distinguishes between familiar (Old) and novel (New) test items.
The example below generates training items based on the XY_GRAMMAR, which alternates Xs and Ys, and grammatical (G) test items that are either Old (included in the training set) or New (not included in training).
s_xy = aglss(xy_grammar, [1 5]); [s, famlevs] = fam_factor(s_xy, 'fam'); [s] = gram_factor(s, 'gram'); s = factorial_testsets(s, [{'fam'}, famlevs], {'gram', 'G'}); s = choose_items(s, 4, 2, [], true); % Training items eligible to use in test disp('Training items:'); disp(format_train_items(s)); disp('Test items:'); disp(format_test_items(s));
Potential items: Grammar involves 2 symbols (xy) 62 possible strings of length 1-5 10 grammatical strings (16.13%) 52 ungrammatical strings (83.87%) Using all 10 grammatical strings Using all 52 ungrammatical strings Choosing training item 1.... Choosing training item 2.... Choosing training item 3.... Choosing training item 4.... Updating potential items.... Choosing test item 1 for each set... 1 2. Choosing test item 2 for each set... 2 1. Training items: Itm_num Itm_name 01 yxyxy 02 yxy 03 y 04 xy Test items: Tset_num fam_cat gram_cat Itm_num Itm_name 01 Old G 01 yxyxy 01 Old G 02 xy 02 New G 01 yxy 02 New G 02 y
Familiarity factor with specified category names
FAM_FACTOR(aglss, 'fname', {'oldname', 'newname'}) specifies alternative names for the Old and New categories.
s = fam_factor(s_xy, 'MyFam', {'Familiar', 'Novel'}); [s] = gram_factor(s, 'gram'); s = factorial_testsets(s, {'MyFam', 'Familiar', 'Novel'}, {'gram', 'G'} ); s = choose_items(s, 4, 2, [], true); disp('Training items:'); disp(format_train_items(s)); disp('Test items:'); disp(format_test_items(s));
Choosing training item 1.... Choosing training item 2.... Choosing training item 3.... Choosing training item 4.... Updating potential items.... Choosing test item 1 for each set... 2 1. Choosing test item 2 for each set... 1 2. Training items: Itm_num Itm_name 01 yxyxy 02 yxy 03 y 04 xy Test items: Tset_num MyFam_cat gram_cat Itm_num Itm_name 01 Familiar G 01 yxy 01 Familiar G 02 y 02 Novel G 01 yxyxy 02 Novel G 02 xy
Dummy familiarity factor
The example below explicitly identifies all test items chosen by StimSelect as being different from any of the training items. Without this factor, test items would still be different from training items in accordance with the default behavior of choose_items(). However, that fact is not explicitly indicated by default when test items are displayed.
s_xy = aglss(xy_grammar, [1 5]); [s, glevs] = gram_factor(s_xy, 'gram'); [s, famlevs] = fam_factor(s, 'fam'); s = factorial_testsets(s, [{'gram'}, glevs], {'fam', 'New'}); s = choose_items(s, 4, 2); disp('Training items:'); disp(format_train_items(s)); disp('Test items:'); disp(format_test_items(s));
Potential items: Grammar involves 2 symbols (xy) 62 possible strings of length 1-5 10 grammatical strings (16.13%) 52 ungrammatical strings (83.87%) Using all 10 grammatical strings Using all 52 ungrammatical strings Choosing training item 1.... Choosing training item 2.... Choosing training item 3.... Choosing training item 4.... Updating potential items.... Choosing test item 1 for each set... 1 2. Choosing test item 2 for each set... 1 2. Training items: Itm_num Itm_name 01 xy 02 xyxy 03 xyxyx 04 yxy Test items: Tset_num gram_cat fam_cat Itm_num Itm_name 01 G New 01 xyx 01 G New 02 yx 02 NG New 01 xxxy 02 NG New 02 xyyy