Data | Direct age-standardization | Modeling age-specific risk | Age-standardizing model results | References
This package is considered a duplicate. The official version of this package is found at:https://connordonegan.r-universe.dev/surveil
Package: surveil 0.3.0
Connor Donegan
surveil: Time Series Models for Disease Surveillance
Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <https://mc-stan.org>; Theil (1972, ISBN:0-444-10378-3).
Authors:
surveil_0.3.0.tar.gz
surveil_0.3.0.zip(r-4.7-x86_64)surveil_0.3.0.zip(r-4.7-arm64)surveil_0.3.0.zip(r-4.6-x86_64)surveil_0.3.0.zip(r-4.6-arm64)
surveil_0.3.0.tar.gz(r-4.7-arm64)surveil_0.3.0.tar.gz(r-4.7-x86_64)surveil_0.3.0.tar.gz(r-4.6-arm64)surveil_0.3.0.tar.gz(r-4.6-x86_64)
surveil_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
surveil/json (API)
| # Install 'surveil' in R: |
| install.packages('surveil', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/connordonegan/surveil/issues
Pkgdown/docs site:https://connordonegan.github.io
Datasets:
Last updated from:106a82755d. Checks:8 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 295 | ||
| linux-devel-x86_64 | NOTE | 247 | ||
| source / vignettes | OK | 435 | ||
| linux-release-arm64 | NOTE | 283 | ||
| linux-release-x86_64 | NOTE | 342 | ||
| windows-devel-arm64 | NOTE | 393 | ||
| windows-devel-x86_64 | NOTE | 439 | ||
| windows-release-arm64 | NOTE | 397 | ||
| windows-release-x86_64 | NOTE | 376 | ||
| wasm-release | OK | 220 |
Exports:apcgroup_difflkjnormalstan_rwstandardizetheiltheil2waic
Dependencies:abindarrayhelpersbackportsBHcallrcheckmateclicodacpp11descdistributionaldplyrfarvergenericsggdistggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrmatrixStatsnumDerivotelpillarpkgbuildpkgconfigposteriorprocessxpspurrrquadprogQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsS7scalesStanHeadersstringistringrsvUnittensorAtibbletidybayestidyrtidyselectutf8vctrsviridisLitewithr
Age-standardized rates
Last update: 2024-07-09
Started: 2022-04-03
MCMC with surveil
Example model | MCMC analysis | Monte Carlo standard errors | Rhat | Divergent transitions | References
Last update: 2024-07-09
Started: 2022-08-22
Measuring health inequality
Concepts | Demonstration | Comparing age-stratified groups | Measuring inequality with multiple groups | References
Last update: 2024-07-09
Started: 2024-07-09
Using surveil for public health research
Getting started | Preparing the data | Model specification | The basics | Binomial model | Fitting the model | Printing results | Visualizing results | Percent change | MCMC diagnostics | Multiple time series | References
Last update: 2024-07-09
Started: 2022-08-22
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The 'surveil' package | surveil-package surveil |
| Annual and cumulative percent change | apc apc.stand_surveil apc.surveil |
| US cancer incidence by age, 1999-2017 | cancer |
| Measures of pairwise inequality | group_diff group_diff.list group_diff.surveil |
| Colorectal cancer incidence by Texas MSA, 1999-2017, ages 50-79 | msa |
| Methods for fitted 'surveil' models | plot.list plot.surveil print.surveil |
| Methods for Theil's index | plot.theil plot.theil_list print.theil print.theil_list |
| Methods for APC objects | plot.apc print.apc |
| Methods for age-standardized rates | plot.stand_surveil print.stand_surveil |
| Prior distributions | lkj normal priors |
| Time series models for mortality and disease incidence | stan_rw |
| 2000 U.S. standard million population | standard |
| Age-standardized rates | standardize |
| Methods for 'surveil_diff' objects | plot.surveil_diff print.surveil_diff surveil_diff |
| Theil's inequality index | theil theil.list theil.surveil theil2 |
| Widely Applicable Information Criteria | waic |