Package: gsearly 1.0.0

gsearly: Creates Group Sequential Trial Designs when Early Outcomes are Available

Methods to construct and power group sequential clinical trial designs for outcomes at multiple times. Outcomes at earlier times provide information on the final (primary) outcome. A range of recruitment and correlation models are available as are methods to simulate data in order to explore design operating characteristics. For more details see Parsons (2024) <doi:10.1186/s12874-024-02174-w>.

Authors:Nick Parsons [aut, cre]

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manual.pdf |manual.html✨
card.svg |card.png
gsearly/json (API)

# Install 'gsearly' in R:

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

Datasets:

qol - Quality of life index for patients with knee pain

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 155 downloads 21 exports 70 dependencies

Last updated from:10cf1abaf1. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	150
source / vignettes	OK	210
linux-release-x86_64	OK	153
macos-release-arm64	OK	208
macos-oldrel-arm64	OK	147
windows-devel	OK	99
windows-release	OK	100
windows-oldrel	OK	104
wasm-release	OK	127

Exports:corrExp corrUnif dataOrder expectSampsize fixedSampsize gsearlyFit gsearlyModel gsearlySimulate gsearlyUser modelParameters plot.gsearly plotBoundary plotInform plotPower plotRecruit print.gsearly print.summary.gsearly roundInterims simdataExtract summary.gsearly tfuStandard

Dependencies:base64enc bigD bitops bslib cachem cli commonmark cpp11 curl digest dplyr evaluate farver fastmap fontawesome fs generics ggplot2 glue gsDesign gt gtable highr htmltools htmlwidgets isoband jquerylib jsonlite juicyjuice knitr labeling lattice lifecycle litedown magrittr markdown memoise mime mvtnorm nlme pillar pkgconfig purrr r2rtf R6 rappdirs RColorBrewer Rcpp reactable reactR rlang rmarkdown S7 sass scales stringi stringr tibble tidyr tidyselect tinytex utf8 V8 vctrs viridisLite withr xfun xml2 xtable yaml

Help page	Topics
Group sequential designs with early outcomes	gsearly-package gsearly
Exponential correlation matrix	corrExp
Uniform correlation matrix	corrUnif
Order a data frame by subject and ordered time variable	dataOrder
Expected sample size for a gsearly model	expectSampsize
Fixed model sample size for a gsearly model	fixedSampsize
Fit a generalized least squares model	gsearlyFit
Model based estimates of sample size and power for group sequential designs with early outcomes	gsearlyModel
Simulates data for a previously fitted gsearly model	gsearlySimulate
User input estimates of sample size and power for group sequential designs with early outcomes	gsearlyUser
Estimates model parameters from raw data	modelParameters
Plot a gsearly model	plot.gsearly
A boundary plot for a gsearly model	plotBoundary
An information plot for a gsearly model	plotInform
A power plot for a gsearly model	plotPower
A recruitment plot for a gsearly model	plotRecruit
Print a gsearly model	print.gsearly
Print a gsearly model summary	print.summary.gsearly
Quality of life index for patients with knee pain	qol
Round a gsearly design interim sample size to integer values	roundInterims
Extract simulated data for a single trial	simdataExtract
Summarise a gsearly model	summary.gsearly
Standardize follow-up times	tfuStandard

Package: gsearly 1.0.0

gsearly: Creates Group Sequential Trial Designs when Early Outcomes are Available

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)