corp_coco | R Documentation |
Calculates statistically significant difference in co-occurrence counts.
corp_coco(A, B, nodes, collocates = NULL, fdr = 0.01) # Deprecated coco(A, B, nodes, fdr = 0.01, collocates = NULL)
A |
A |
B |
A |
nodes |
A |
collocates |
A |
fdr |
The desired level at which to control the False Discovery Rate.
Default value is |
The corp_coco function implements the method introduced in Wiegand and Hennessey et al. (2017a) (described in more detail from a linguistic perspective in Wiegand, 2019).
fdr indicates the level at which the False Discovery Rate will be
controlled because the method carries out a large number of tests.
For a description of the form of FDR used see Benjamini and Hochberg (1995).
For description of the p_adjusted column in the returned structure see
p.adjust
.
The returned data structure is a data.table
.
A data.table
is also a data.frame
and will behave exactly
as such if the data.table
library is not loaded.
The returned data.table
contains details of all the
co-occurrences for which there is evidence of a difference in
co-occurrence between the two supplied data sets.
The effect size is calculated as the log base 2 of the odds ratio.
The effects size and its confidence interval are captured in the
effect_size, CI_lower and CI_upper columns.
The p_value column contains the non-adjusted p-value from the
Fisher's Exact Test.
A data.table
of the form
Classes ‘data.table’ and 'data.frame': 11 variables: $ x : chr $ y : chr $ H_A : int $ M_A : int $ H_B : int $ M_B : int $ effect_size : num $ CI_lower : num $ CI_upper : num $ p_value : num $ p_adjusted : num - attr(*, "sorted")= chr "x" "y" - attr(*, ".internal.selfref")=<externalptr> - attr(*, "coco_metadata")=List of 5 ..$ nodes : chr ..$ collocates : chr ..$ fdr : num ..$ PACKAGE_VERSION:Classes 'package_version', 'numeric_version' .. ..$ : int ..$ date : Date, format: "2016-11-01"
Y. Benjamini and Y. Hochberg (1995) Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 57 (1)289–300.
* Wiegand, V., Hennessey, A., Tench, C. R., & Mahlberg, M. (2017a, May 24). Comparing co-occurrences between corpora. 38th ICAME conference, Charles University, Prague. * Wiegand, V. (2019). A Corpus Linguistic Approach to Meaning-Making Patterns in Surveillance Discourse [PhD, University of Birmingham]. https://etheses.bham.ac.uk/id/eprint/9778
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