Package: afdx 1.1.2

afdx: Diagnosis Performance Using Attributable Fraction
Estimate diagnosis performance (Sensitivity, Specificity, Positive predictive value, Negative predicted value) of a diagnostic test where can not measure the golden standard but can estimate it using the attributable fraction.
Authors:
afdx_1.1.2.tar.gz
afdx_1.1.2.zip(r-4.7-any)afdx_1.1.2.zip(r-4.6-any)afdx_1.1.2.zip(r-4.5-any)
afdx_1.1.2.tgz(r-4.6-any)afdx_1.1.2.tgz(r-4.5-any)
afdx_1.1.2.tar.gz(r-4.7-any)afdx_1.1.2.tar.gz(r-4.6-any)
afdx_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
afdx/json (API)
| # Install 'afdx' in R: |
| install.packages('afdx', repos = c('https://johnaponte.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/johnaponte/afdx/issues
Pkgdown/docs site:https://johnaponte.github.io
- malaria_df1 - Synthetic data simulating a malaria crossectional
- malaria_df2 - Synthetic data simulating a malaria crossectional
Last updated from:dcbc5f0196. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 136 | ||
| source / vignettes | OK | 183 | ||
| linux-release | OK | 144 | ||
| macos-release | OK | 183 | ||
| macos-oldrel | OK | 141 | ||
| windows-devel | OK | 87 | ||
| windows-release | OK | 89 | ||
| windows-oldrel | OK | 99 | ||
| wasm-release | OK | 115 |
Exports:get_latent_modellogitexpmake_cutoffsmake_n_cutoffssenspec
Dependencies:clicpp11digestdplyrgenericsgluelatticelifecyclemagrittrmaxLikmiscToolspillarpkgconfigpurrrR6rlangsandwichstringistringrtibbletidyrtidyselectutf8vctrswithrzoo
Last update: 2026-03-06
Started: 2021-02-07
Last update: 2026-03-06
Started: 2021-02-01
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| afdx: Diagnosis performance indicators from attributable fraction estimates. | afdx-package afdx |
| Template for the bayesian latent class model | get_latent_model |
| Exponential logit model for two variables | logitexp |
| Cut-off points for densities and fever | make_cutoffs |
| Make a defined number of categories having similar number of positives in each category | make_n_cutoffs |
| Synthetic data simulating a malaria crossectional | malaria_df1 |
| Synthetic data simulating a malaria crossectional | malaria_df2 |
| S3 methods to estimate diagnosis performance of an afmodel | senspec senspec.afmodel senspec.default |