3,151 to 3,160 of 11,020 Results
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Plain Text - 25.0 KB -
MD5: 59f0e6205722082c189644cf640b854b
mixed-effects generalized additive model (GAMM) for accuracy, and visualizations of the results |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
R Data - 309.0 KB -
MD5: 5305268bb0abaf0d3a129ce48a983aa3
R data frames sall_results, sall_clean, sall_items, sall_target |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Plain Text - 30.6 KB -
MD5: a15ee576d24ea22b34c1ea5eabd5b971
mixed-effects generalized additive model (GAMM) for response times, and visualizations of the results |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Tabular Data - 562.0 KB - 31 Variables, 2781 Observations - UNF:6:9i7F5I6FRlXgGVaNe1UzrQ==
includes only ‘correct’ responses |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Tabular Data - 361.2 KB - 25 Variables, 1596 Observations - UNF:6:dKyFgZ2A1dA3cX4/D8gKjA==
includes only target items [i.e. no control and distractor items], responses marked for 'correct' (yes/no) |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Tabular Data - 585.8 KB - 29 Variables, 3192 Observations - UNF:6:SckM1Rs9ZcBHngUF9hmZaQ==
the complete ‘raw’ data |
Jun 6, 2019 -
Replication data for: Chunking or predicting – frequency information and reduction in the perception of multi-word sequences
Tabular Data - 344.2 KB - 26 Variables, 1367 Observations - UNF:6:H947lcKHGCtYINvOUArC0w==
includes only correct responses on target items |
Feb 13, 2024
Verroens, Filip, 2024, "Replication Data for: Zooming in on the semantics of French ingressives: a collostructional analysis", https://doi.org/10.18710/SZZDLI, DataverseNO, V1
Dataset abstract: The dataset includes an annotated corpus sample of N = 2000 French sentences with se mettre à or commencer à (1000 observations of each verb). The sample was drawn from the literary corpus Frantext and the journalistic corpus Le Monde (1000 observations from both corpora). The sample is balanced for verb as well as corpus, so we h... |
Feb 13, 2024 -
Replication Data for: Zooming in on the semantics of French ingressives: a collostructional analysis
Plain Text - 8.8 KB -
MD5: e11c4a1f45dabb8f10e017d74fda5d5c
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Feb 13, 2024 -
Replication Data for: Zooming in on the semantics of French ingressives: a collostructional analysis
Comma Separated Values - 88.6 KB -
MD5: 0c5a6c1d8fc1e630c2557c55b7d13055
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