Package: afdx 1.1.1
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_1.1.1.tar.gz
afdx_1.1.1.zip(r-4.5)afdx_1.1.1.zip(r-4.4)afdx_1.1.1.zip(r-4.3)
afdx_1.1.1.tgz(r-4.4-any)afdx_1.1.1.tgz(r-4.3-any)
afdx_1.1.1.tar.gz(r-4.5-noble)afdx_1.1.1.tar.gz(r-4.4-noble)
afdx_1.1.1.tgz(r-4.4-emscripten)afdx_1.1.1.tgz(r-4.3-emscripten)
afdx.pdf |afdx.html✨
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
- malaria_df1 - Synthetic data simulating a malaria crossectional
- malaria_df2 - Synthetic data simulating a malaria crossectional
Last updated 4 years agofrom:8bd170b3de. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 03 2024 |
R-4.5-win | NOTE | Nov 03 2024 |
R-4.5-linux | NOTE | Nov 03 2024 |
R-4.4-win | NOTE | Nov 03 2024 |
R-4.4-mac | NOTE | Nov 03 2024 |
R-4.3-win | NOTE | Nov 03 2024 |
R-4.3-mac | NOTE | Nov 03 2024 |
Exports:get_latent_modellogitexpmake_cutoffsmake_n_cutoffssenspec
Dependencies:clicpp11digestdplyrfansigenericsgluelatticelifecyclemagrittrmaxLikmiscToolspillarpkgconfigpurrrR6rlangsandwichstringistringrtibbletidyrtidyselectutf8vctrswithrzoo
Attributable fraction using a latent class model
Rendered fromlatentclass.Rmd
usingknitr::rmarkdown
on Nov 03 2024.Last update: 2021-05-23
Started: 2021-02-07
Attributable fraction using a logitexponetial model
Rendered fromaf_logit_exponential.Rmd
usingknitr::rmarkdown
on Nov 03 2024.Last update: 2021-03-20
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 |