Package: testerror 0.1.0

Robert Challen

testerror: Uncertainty in Multiplex Panel Testing

Provides methods to support the estimation of epidemiological parameters based on the results of multiplex panel tests.

Authors:Robert Challen [aut, cre]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
testerror/json (API)

# Install 'testerror' in R:
install.packages('testerror', repos = c('https://bristol-vaccine-centre.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bristol-vaccine-centre/testerror/issues

On CRAN:

Conda:

3.40 score 1 stars 6 scripts 43 exports 80 dependencies

Last updated from:4420c57e70 (on 0.1.0). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK293
source / vignettesOK678
linux-release-x86_64OK240
macos-release-arm64OK227
macos-oldrel-arm64OK181
windows-develOK298
windows-releaseOK364
windows-oldrelOK323
wasm-releaseOK196

Exports:.input_data.input_panel_data.output_data%>%apparent_prevalencebayesian_component_logit_modelbayesian_component_simpler_modelbayesian_panel_complex_modelbayesian_panel_logit_modelbayesian_panel_simpler_modelbayesian_panel_true_prevalence_modelbayesian_true_prevalence_modelbeta_distbeta_fitbeta_paramsci_to_logitnormfp_p_valuefp_signif_levelget_beta_shapeinv_logitlogitodds_ratio_veoptimal_performancepanel_prevalencepanel_senspanel_sens_estimatorpanel_specprevalence_lang_reiczigelprevalence_panel_lang_reiczigelrelative_risk_verogan_gladensens_priorspec_priortrue_panel_prevalencetrue_prevalenceuncertain_panel_rogan_gladenuncertain_panel_sens_estimatoruncertain_panel_specuncertain_rogan_gladenunderestimation_thresholduniform_prioruninformed_priorupdate_posterior

Dependencies:abindbackportsBHbrewcachemcallrcheckmateclicommonmarkcpp11crayondescdigestdistributionaldplyrevaluateextraDistrfarverfastmapforcatsfsgenericsggplot2gluegridExtragtablehighrinlineinterfacerisobandknitrlabelinglifecyclelobstrloolubridatemagrittrmatrixStatsmemoisenumDerivotelpillarpkgbuildpkgconfigpkgloadpkgutilsposteriorprettyunitsprocessxpspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangroxygen2rprojrootrstanS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselecttimechangeutf8vctrsviridisLitewithrxfunxml2yaml

Getting started
Correcting panel tests for test error
Rendered fromtesterror.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2023-03-02

Panel test error adjustment
Rendered frompanel-tests.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2023-08-10

Single test error adjustment
Rogan-gladen adjustment | BinaxNOW Example | Test uncertainty
Rendered fromsingle-test.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2023-08-10

Bayesian adjustment of panel test error
BinaxNOW test results | UAD1 results | Sensitivity analysis with different UAD test parameters
Rendered frombayesian-panel-tests.Rmdusingknitr::rmarkdown

Last update: 2023-08-31
Started: 2023-08-10

Working with Beta distributions
Rendered frombeta-distributions.Rmdusingknitr::rmarkdown

Last update: 2023-08-21
Started: 2023-08-10

Readme and manuals

Help Manual

Help pageTopics
Dataframe format for component test results.input_data
Dataframe format for panel test results.input_panel_data
Dataframe format for true prevalence results.output_data
Apparent prevalence from known prevalenceapparent_prevalence
convert a beta distribution to a tibbleas_tibble.beta_dist
convert a list of betas to a tibbleas_tibble.beta_dist_list
Bayesian simpler model true prevalence for componentbayesian_component_logit_model
Bayesian simpler model true prevalence for componentbayesian_component_simpler_model
Bayesian models true prevalence for panelbayesian_panel_complex_model
Bayesian logit model true prevalence for panelbayesian_panel_logit_model
Bayesian simpler model true prevalence for panelbayesian_panel_simpler_model
Execute one of a set of bayesian modelsbayesian_panel_true_prevalence_model
Execute one of a set of bayesian modelsbayesian_true_prevalence_model
Generate a beta distribution out of probabilities, or positive and negative countsbeta_dist
Fit a beta distribution to data using method of momentsbeta_fit
Generate concave beta distribution parameters from mean and confidence intervalsbeta_params
Generate mu and sigma parameters for a logitnormal distributionci_to_logitnorm
Format a beta distributionformat.beta_dist
Format a beta distribution listformat.beta_dist_list
Significance of an uncertain test resultfp_p_value
Identify the minimum number of positive test result observations needed to be confident the disease has a non-zero prevalence.fp_signif_level
Get a parameter of the 'beta_dist'get_beta_shape
Get a parameter of the 'beta_dist'get_beta_shape.beta_dist
Get a parameter of the 'beta_dist'get_beta_shape.beta_dist_list
The inverse logit functioninv_logit
Detect the length of a beta distributionlength.beta_dist
Detect the length of a beta distribution listlength.beta_dist_list
The logit functionlogit
Calculate a vaccine effectiveness estimate based on an odds ratioodds_ratio_ve
Test optimal performanceoptimal_performance
Expected test panel prevalence assuming independencepanel_prevalence
Test panel combination sensitivitypanel_sens
Estimate test panel combination sensitivitypanel_sens_estimator
Test panel combination specificitypanel_spec
True prevalence from apparent prevalence with uncertaintyprevalence_lang_reiczigel
Lang-Reiczigel true prevalence for panelprevalence_panel_lang_reiczigel
Print a beta distributionprint.beta_dist
Print a beta distributionprint.beta_dist_list
Calculate a vaccine effectiveness estimate based on a risk ratiorelative_risk_ve
Repeat a 'beta_dist'rep.beta_dist
True prevalence from apparent prevalencerogan_gladen
The default prior for specificitysens_prior
The default prior for specificityspec_prior
Calculate an estimate of true prevalence for a single panel and componentstrue_panel_prevalence
Vectorised true prevalence estimatestrue_prevalence
Rogan-Gladen true prevalence for panel with resamplinguncertain_panel_rogan_gladen
Propagate component test sensitivity and specificity into panel specificity assuming a known set of observations of component apparent prevalenceuncertain_panel_sens_estimator
Propagate component test specificity into panel specificityuncertain_panel_spec
True prevalence from apparent prevalence with uncertaintyuncertain_rogan_gladen
Test underestimation limitunderestimation_threshold
A uniform prioruniform_prior
Uninformative prioruninformed_prior
Update the posterior of a 'beta_dist'update_posterior
Update the posterior of a 'beta_dist'update_posterior.beta_dist
Update the posterior of a 'beta_dist'update_posterior.beta_dist_list