tidylo: Weighted Tidy Log Odds Ratio
How can we measure how the usage or frequency of some
feature, such as words, differs across some group or set, such as
documents? One option is to use the log odds ratio, but the log odds
ratio alone does not account for sampling variability; we haven't
counted every feature the same number of times so how do we know which
differences are meaningful? Enter the weighted log odds, which
'tidylo' provides an implementation for, using tidy data principles.
In particular, here we use the method outlined in Monroe, Colaresi,
and Quinn (2008) <doi:10.1093/pan/mpn018> to weight the log odds ratio
by a prior. By default, the prior is estimated from the data itself,
an empirical Bayes approach, but an uninformative prior is also
available.
| Version: |
0.2.0 |
| Imports: |
dplyr, rlang |
| Suggests: |
covr, ggplot2, janeaustenr, knitr, rmarkdown, stringr, testthat (≥ 2.1.0), tidytext |
| Published: |
2022-03-22 |
| DOI: |
10.32614/CRAN.package.tidylo |
| Author: |
Tyler Schnoebelen [aut],
Julia Silge  [aut,
cre, cph],
Alex Hayes [aut] |
| Maintainer: |
Julia Silge <julia.silge at gmail.com> |
| BugReports: |
https://github.com/juliasilge/tidylo/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://juliasilge.github.io/tidylo/,
https://github.com/juliasilge/tidylo |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
tidylo results |
Documentation:
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