Package: emery 0.5.1

Corie Drake

emery: Accuracy Statistic Estimation for Imperfect Gold Standards

Produce maximum likelihood estimates of common accuracy statistics for multiple measurement methods when a gold standard is not available. An R implementation of the expectation maximization algorithms described in Zhou et al. (2011) <doi:10.1002/9780470906514> with additional functions for creating simulated data and visualizing results. Supports binary, ordinal, and continuous measurement methods.

Authors:Corie Drake [aut, cre, cph]

emery_0.5.1.tar.gz
emery_0.5.1.tar.gz(r-4.5-noble)emery_0.5.1.tar.gz(r-4.4-noble)
emery_0.5.1.tgz(r-4.4-emscripten)emery_0.5.1.tgz(r-4.3-emscripten)
emery.pdf |emery.html
emery/json (API)
NEWS

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

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 1 scripts 141 downloads 19 exports 39 dependencies

Last updated 10 months agofrom:fedda1b415. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 17 2024
R-4.5-linuxOKDec 17 2024

Exports:boot_MLestimate_MLestimate_ML_binaryestimate_ML_continuousestimate_ML_ordinalgenerate_multimethod_binarygenerate_multimethod_continuousgenerate_multimethod_datagenerate_multimethod_ordinalplotplot_MLplot_ML_binaryplot_ML_continuousplot_ML_ordinalpollinate_MLpollinate_ML_binarypollinate_ML_continuouspollinate_ML_ordinalshow

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigpurrrR6rbibutilsRColorBrewerRdpackrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

emery

Rendered fromemery.Rmdusingknitr::rmarkdownon Dec 17 2024.

Last update: 2024-02-21
Started: 2024-02-21

Readme and manuals

Help Manual

Help pageTopics
Bootstrap ML accuracy statistic estimation for multi-method databoot_ML
Censor data randomly rowwisecensor_data
Define the True disease state of a simulated sampledefine_disease_state
Estimate maximum likelihood accuracy statistics by expectation maximizationestimate_ML estimate_ML_binary estimate_ML_continuous estimate_ML_ordinal
Create data sets which simulate paired measurements of multiple methodsgenerate_multimethod_binary generate_multimethod_continuous generate_multimethod_data generate_multimethod_ordinal
S4 object containing the results of multi-method ML accuracy estimatesMultiMethodMLEstimate-class
Create unique names for a set of thingsname_thing
Create plots visualizing the ML estimation process and results.plot_ML plot_ML_binary plot_ML_continuous plot_ML_ordinal
Create plots from a MultiMethodMLEstimate objectplot,MultiMethodMLEstimate-method
Generate seed values for EM algorithmpollinate_ML pollinate_ML_binary pollinate_ML_continuous pollinate_ML_ordinal
Show a MultiMethodMLEstimate S4 objectshow,MultiMethodMLEstimate-method