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bennu

BayesianEstimation ofNaloxoneNumbersUnderreporting (BENNU)

The package name comes from the Welsh word for “to finish”(pronounced benn-y)

R-CMD-checkLifecycle: experimentalCodecov test coverageGitHub

An R package 📦 for generating estimates of total naloxone kitnumbers distributed and used from naloxone kit orders data.

Installation

You can install the released version of bennu fromCRAN with:

install.packages("bennu")

And the development version fromGitHub with:

# install.packages("devtools")devtools::install_github("sempwn/bennu")

Example

This example runs output for test data generated by the package:

library(bennu)library(rstan)#> Loading required package: StanHeaders#>#> rstan version 2.32.7 (Stan version 2.32.2)#> For execution on a local, multicore CPU with excess RAM we recommend calling#> options(mc.cores = parallel::detectCores()).#> To avoid recompilation of unchanged Stan programs, we recommend calling#> rstan_options(auto_write = TRUE)#> For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,#> change `threads_per_chain` option:#> rstan_options(threads_per_chain = 1)library(bayesplot)#> This is bayesplot version 1.14.0#> - Online documentation and vignettes at mc-stan.org/bayesplot#> - bayesplot theme set to bayesplot::theme_default()#>    * Does _not_ affect other ggplot2 plots#>    * See ?bayesplot_theme_set for details on theme settingrstan_options(auto_write =TRUE)options(mc.cores = parallel::detectCores(logical =FALSE))## basic example coded<-generate_model_data()# note iter should be at least 2000 to generate a reasonable posterior samplefit<-est_naloxone(d,iter=500)mcmc_pairs(fit,pars =c("sigma","mu0","zeta"),off_diag_args =list(size =1,alpha =0.5))

An overall summary of the model output can also be provided as a dataframe

kit_summary_table(fit,data = d)#> # A tibble: 1 × 6#>   Probability of kit use if dist…¹ Estimated as distrib…² Proportion kits dist…³#>   <glue>                           <glue>                 <glue>#> 1 64.97% (95% CrI: 12.93% - 96.79… 24,907.00 (95% CrI: 2… 21.03% (95% CrI: 20.8…#> # ℹ abbreviated names: ¹​`Probability of kit use if distributed`,#> #   ²​`Estimated as distributed`,#> #   ³​`Proportion kits distributed that are reported`#> # ℹ 3 more variables: `Estimated kits used` <glue>,#> #   `Proportion kits used that are reported` <glue>,#> #   `Proportion kits ordered that are used` <glue>

Getting help

If you encounter a clear bug, please file an issue with a minimalreproducible example onGitHub.


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