Package: coarseDataTools 0.7.1

coarseDataTools: Analysis of Coarsely Observed Data

Functions to analyze coarse data. Specifically, it contains functions to (1) fit parametric accelerated failure time models to interval-censored survival time data, and (2) estimate the case-fatality ratio in scenarios with under-reporting. This package's development was motivated by applications to infectious disease: in particular, problems with estimating the incubation period and the case fatality ratio of a given disease. Sample data files are included in the package. See Reich et al. (2009) <doi:10.1002/sim.3659>, Reich et al. (2012) <doi:10.1111/j.1541-0420.2011.01709.x>, and Lessler et al. (2009) <doi:10.1016/S1473-3099(09)70069-6>.

Authors:Nicholas G. Reich [aut, cre], Justin Lessler [aut], Andrew Azman [aut], Zhian N. Kamvar [ctb], Hugo Gruson [ctb]

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coarseDataTools.pdf |coarseDataTools.html✨
coarseDataTools/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/nickreich/coarsedatatools/issues

Datasets:
  • exp.win.lengths - Exposure window lengths from an influenza outbreak at a NYC school
  • fluA.inc.per - Coarse incubation period data for influenza A
  • nycH1N1 - Incubation period data from New York City Public Schools, 2009 H1N1 influenza outbreak
  • simulated.outbreak.deaths - Simulated case and death reports from a fictional outbreak

On CRAN:

7.97 score 9 stars 8 packages 34 scripts 1.0k downloads 5 mentions 10 exports 10 dependencies

Last updated 1 years agofrom:fe784b1241. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winNOTENov 20 2024
R-4.5-linuxNOTENov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:dic.fitdic.fit.mcmcEMforCFRgenerate.coarse.dataget.obs.typelogLikloglikhdprecision.simulationprecision.simulation.coarseprecision.simulation.exact

Dependencies:codalatticeMASSMatrixMatrixModelsmcmcMCMCpackquantregSparseMsurvival

Using outbreak data to estimate the relative case fatality ratio

Nicholas G Reich

Rendered fromCFR_vignette.Rmdusingknitr::knitron Nov 20 2024.

Last update: 2023-04-28
Started: 2021-12-07

Readme and manuals

Help Manual

Help pageTopics
An S4 Class that stores a fitted coarse data objectcd.fit cd.fit-class
An S4 Class that stores a MCMC fit coarse data objectcd.fit.mcmc cd.fit.mcmc-class
Function that calculates dgamma with a offset of 1 (i.e., 1 is equivalent to 0)dgammaOff1
censored survival datadic.fit
Fits the distribution to the passed-in data using MCMC as implemented in MCMCpack.dic.fit.mcmc
A function to estimate the relative case fatality ratio when reporting rates are time-varying and deaths are lagged because of survival time.EMforCFR
Exposure window lengths from an influenza outbreak at a NYC schoolexp.win.lengths
Coarse incubation period data for influenza AfluA.inc.per
Tries to guess the observation types (SIC, DIC, or exact).get.obs.type
Get the log-likelihood value of a 'cd.fit' or 'cd.fit.mcmc' objectlogLik logLik,cd.fit-method
Negative log likelihood for a dataset of interval-censored data, given a distribution and its parameters.loglikhd
Does a metropolis hastings for the Erlang distributionmcmc.erlang
posterior log likelihood function to pass to MCMCpack samplermcmcpack.ll
Incubation period data from New York City Public Schools, 2009 H1N1 influenza outbreaknycH1N1
Function that calculates pgamma with a offset of 1 (i.e., 1 is equivalent to 0)pgammaOff1
Simulate incubation period analyses with coarse datagenerate.coarse.data precision.simulation precision.simulation.coarse precision.simulation.exact
Simulated case and death reports from a fictional outbreaksimulated.outbreak.deaths