citestR: Conditional Independence of Missingness Test
Tests whether missingness in explanatory variables is
conditionally independent of the outcome, given observed data. Uses
multiply-imputed datasets and cross-validated classifiers to produce a
test statistic and p-value, with a sensitivity parameter (kappa) for
calibrating interpretation. Wraps the 'citest' 'Python' engine via a
local 'FastAPI' server over 'HTTP', so no 'reticulate' dependency is
needed at runtime.
| Version: |
0.1.1 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
curl, httr2 (≥ 1.0.0), processx (≥ 3.8.0), rlang (≥ 1.1.0) |
| Suggests: |
arrow, jsonlite, reticulate, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-03-23 |
| DOI: |
10.32614/CRAN.package.citestR (may not be active yet) |
| Author: |
Thomas Robinson [aut, cre],
Ranjit Lall [aut] |
| Maintainer: |
Thomas Robinson <t.robinson7 at lse.ac.uk> |
| BugReports: |
https://github.com/midasverse/citest/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/midasverse/citest |
| NeedsCompilation: |
no |
| SystemRequirements: |
Python (>= 3.9) with the 'midasverse-citest-api'
package |
| Materials: |
NEWS |
| CRAN checks: |
citestR results |
Documentation:
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