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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testerror.pdf |testerror.html✨
testerror/json (API)

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

Peer review:

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

On CRAN:

4.00 score 1 stars 4 scripts 43 exports 82 dependencies

Last updated 8 months agofrom:4420c57e70 (on 0.1.0). Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 29 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 29 2024
R-4.4-winOKOct 29 2024
R-4.4-macOKOct 29 2024
R-4.3-winOKOct 29 2024
R-4.3-macOKOct 29 2024

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:abindbackportsBHbrewcachemcallrcheckmateclicolorspacecommonmarkcpp11descdigestdistributionaldplyrevaluateextraDistrfansifarverfastmapforcatsfsgenericsggplot2gluegridExtragtablehighrinlineinterfacerisobandknitrlabelinglatticelifecycleloolubridatemagrittrMASSMatrixmatrixStatsmemoisemgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigpkgloadpkgutilsposteriorprocessxpspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelrlangroxygen2rprojrootrstanscalesStanHeadersstringistringrtensorAtibbletidyrtidyselecttimechangeutf8vctrsviridisLitewithrxfunxml2yaml

Bayesian adjustment of panel test error

Rendered frombayesian-panel-tests.Rmdusingknitr::rmarkdownon Oct 29 2024.

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

Getting started

Rendered fromtesterror.Rmdusingknitr::rmarkdownon Oct 29 2024.

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

Panel test error adjustment

Rendered frompanel-tests.Rmdusingknitr::rmarkdownon Oct 29 2024.

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

Single test error adjustment

Rendered fromsingle-test.Rmdusingknitr::rmarkdownon Oct 29 2024.

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

Working with Beta distributions

Rendered frombeta-distributions.Rmdusingknitr::rmarkdownon Oct 29 2024.

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