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Performs drug demand forecasting by modeling drug dispensing data while taking into account predicted enrollment and treatment discontinuation dates. The gap time between randomization and the first drug dispensing visit is modeled using interval-censored exponential, Weibull, log-logistic, or log-normal distributions (Anderson-Bergman (2017) <doi:10.18637/jss.v081.i12>). The number of skipped visits is modeled using Poisson, zero-inflated Poisson, or negative binomial distributions (Zeileis, Kleiber & Jackman (2008) <doi:10.18637/jss.v027.i08>). The gap time between two consecutive drug dispensing visits given the number of skipped visits is modeled using linear regression based on least squares or least absolute deviations (Birkes & Dodge (1993, ISBN:0-471-56881-3)). The number of dispensed doses is modeled using linear or linear mixed-effects models (McCulloch & Searle (2001, ISBN:0-471-19364-X)).
Version: | 0.1.3 |
Depends: | R (≥ 3.5.0) |
Imports: | Rcpp (≥ 1.0.10), dplyr (≥ 1.1.0), rlang (≥ 1.1.0), purrr (≥ 1.0.2), stringr (≥ 1.4.0), plotly (≥ 4.10.1), survival (≥ 2.41-3), mvtnorm (≥ 1.1-3), erify (≥ 0.4.0), stats (≥ 3.5.0), MASS (≥ 7.3-54), nlme (≥ 3.1-153), L1pack (≥ 0.41-24), eventPred (≥ 0.2.3), parallel (≥ 4.1.2), foreach (≥ 1.5.2), doParallel (≥ 1.0.17), doRNG (≥ 1.8.6) |
LinkingTo: | Rcpp |
Published: | 2024-02-28 |
DOI: | 10.32614/CRAN.package.drugDemand |
Author: | Kaifeng Lu [aut, cre] |
Maintainer: | Kaifeng Lu <kaifenglu at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | NEWS |
CRAN checks: | drugDemand results |
Reference manual: | drugDemand.pdf |
Package source: | drugDemand_0.1.3.tar.gz |
Windows binaries: | r-devel: drugDemand_0.1.3.zip, r-release: drugDemand_0.1.3.zip, r-oldrel: drugDemand_0.1.3.zip |
macOS binaries: | r-release (arm64): drugDemand_0.1.3.tgz, r-oldrel (arm64): drugDemand_0.1.3.tgz, r-release (x86_64): drugDemand_0.1.3.tgz, r-oldrel (x86_64): drugDemand_0.1.3.tgz |
Old sources: | drugDemand archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.