Package: beastt 0.0.3

Christina Fillmore

beastt: Bayesian Evaluation, Analysis, and Simulation Software Tools for Trials

Bayesian dynamic borrowing with covariate adjustment via inverse probability weighting for simulations and data analyses in clinical trials. This makes it easy to use propensity score methods to balance covariate distributions between external and internal data.

Authors:Christina Fillmore [aut, cre], Ben Arancibia [aut], Nate Bean [aut], Abi Terry [aut], GlaxoSmithKline Research & Development Limited [cph, fnd], Trustees of Columbia University [cph]

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

# Install 'beastt' in R:

install.packages('beastt', repos = c('https://gsk-biostatistics.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gsk-biostatistics/beastt/issues

Pkgdown site:https://gsk-biostatistics.github.io

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

ex_binary_df - External Binary Control Data for Propensity Score Balancing
ex_norm_df - External Normal Control Data for Propensity Score Balancing
ex_tte_df - External Time-to-Event Control Data for Propensity Score Balancing
int_binary_df - Internal Binary Data for Propensity Score Balancing
int_norm_df - Internal Normal Data for Propensity Score Balancing
int_tte_df - Internal Time-to-Event Control Data for Propensity Score Balancing

On CRAN:

cpp

6.67 score 3 stars 4 scripts 293 downloads 24 exports 102 dependencies

Last updated 19 hours agofrom:d1b9c95ade. Checks:1 OK, 11 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 31 2025
R-4.5-win-x86_64	NOTE	Mar 31 2025
R-4.5-mac-x86_64	NOTE	Mar 31 2025
R-4.5-mac-aarch64	NOTE	Mar 31 2025
R-4.5-linux-x86_64	NOTE	Mar 31 2025
R-4.4-win-x86_64	NOTE	Mar 31 2025
R-4.4-mac-x86_64	NOTE	Mar 31 2025
R-4.4-mac-aarch64	NOTE	Mar 31 2025
R-4.4-linux-x86_64	NOTE	Mar 31 2025
R-4.3-win-x86_64	NOTE	Mar 31 2025
R-4.3-mac-x86_64	NOTE	Mar 31 2025
R-4.3-mac-aarch64	NOTE	Mar 31 2025

Exports:bootstrap_cov calc_cond_binary calc_post_beta calc_post_norm calc_post_weibull calc_power_prior_beta calc_power_prior_norm calc_power_prior_weibull calc_prop_scr glance inv_logit is_prop_scr mix_means mix_sigmas plot_dist prop_scr_cloud prop_scr_dens prop_scr_hist prop_scr_love rescale robustify_mvnorm robustify_norm tidy trim

Dependencies:abind askpass backports base64enc BH bslib cachem callr checkmate chk cli cobalt colorspace cpp11 crayon crosstalk curl data.table desc digest distributional dplyr evaluate fansi farver fastmap fontawesome fs generics ggdist ggplot2 glue gridExtra gtable highr htmltools htmlwidgets httr inline isoband jquerylib jsonlite kernlab knitr labeling later lattice lazyeval lifecycle loo magrittr MASS Matrix matrixStats memoise mgcv mime mixtools munsell nlme numDeriv openssl pillar pkgbuild pkgconfig plotly posterior processx promises ps purrr quadprog QuickJSR R6 rappdirs RColorBrewer Rcpp RcppEigen RcppParallel rlang rmarkdown rstan rstantools sass scales segmented StanHeaders stringi stringr survival sys tensorA tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Binary Outcome

Rendered frombinary.Rmdusingknitr::rmarkdownon Mar 31 2025.

Last update: 2024-12-17
Started: 2024-06-14

Normal Outcome (Known SD)

Rendered fromcontinuous.Rmdusingknitr::rmarkdownon Mar 31 2025.

Last update: 2025-01-24
Started: 2024-02-08

Time-to-Event Outcome

Rendered fromtte.Rmdusingknitr::rmarkdownon Mar 31 2025.

Last update: 2025-01-24
Started: 2024-12-10

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The 'beastt' package.	beastt-package beastt
Bootstrap Covariate Data	bootstrap_cov
Calculate Conditional Drift and Treatment Effect for Binary Outcome Models	calc_cond_binary
Calculate Posterior Beta	calc_post_beta
Calculate Posterior Normal	calc_post_norm
Calculate Posterior Weibull	calc_post_weibull
Calculate Power Prior Beta	calc_power_prior_beta
Calculate Power Prior Normal	calc_power_prior_norm
Calculate Power Prior Weibull	calc_power_prior_weibull
Create a Propensity Score Object	calc_prop_scr
External Binary Control Data for Propensity Score Balancing	ex_binary_df
External Normal Control Data for Propensity Score Balancing	ex_norm_df
External Time-to-Event Control Data for Propensity Score Balancing	ex_tte_df
Internal Binary Data for Propensity Score Balancing	int_binary_df
Internal Normal Data for Propensity Score Balancing	int_norm_df
Internal Time-to-Event Control Data for Propensity Score Balancing	int_tte_df
Inverse Logit Function	inv_logit
Test If Propensity Score Object	is_prop_scr
Extract Means of Mixture Components	mix_means
Extract Standard Deviations of Mixture Components	mix_sigmas
Plot Distribution	plot_dist
Propensity Score Cloud Plot	prop_scr_cloud
Density of the Propensity Score Object	prop_scr_dens
Histogram of the Propensity Score Object	prop_scr_hist
Love Plot of the Absolute Standardized Mean Differences	prop_scr_love
Rescale a 'prop_scr' object	rescale
Robustify Multivariate Normal Distributions	robustify_mvnorm
Robustify Normal Distributions	robustify_norm
Tidy a(n) prop_scr object	tidy.prop_scr
Trim a 'prop_scr' object	trim