RCTRecruit-package: RCTRecruit: Non-Parametric Recruitment Prediction for...

In RCTRecruit: Non-Parametric Recruitment Prediction for Randomized Clinical Trials

RCTRecruit: Non-Parametric Recruitment Prediction for Randomized Clinical Trials

Description

Accurate prediction of subject recruitment for Randomized Clinical Trials (RCT) remains an ongoing challenge. Many previous prediction models rely on parametric assumptions. We present functions for non-parametric RCT recruitment prediction under several scenarios.

Details

Package:	RCTRecruit
Type:	Package
Version:	0.2.0
Date:	2025-04-21
License:	MIT + file LICENSE
Functions:
	GetDistance	Euclidean distance between predicted and actual recruitment
	GetWeekPredCI	Calculate median recruitment with 95% CI for the next 104 weeks (two years)
	LoadData	Load recruitment data.
	plot.RCTPredCI	Plots RCTPredCI object
	Time2Nsubjects	Simulate the number of weeks needed to recruit a given number of subjects
Datasets:
	gripsYR1	Daily recruitment data for the 1st year of the GRIPS study
	gripsYR2	Daily recruitment data for the 2nd year of the GRIPS study
	gripsYR2Weekly	Weekly recruitment data for the 2nd year of the GRIPS study

Author(s)

Maintainer: Ioannis Malagaris [e-mail] (ORCID) [copyright holder]

Authors:

• Alejandro Villasante-Tezanos [e-mail]

• Christopher Kurinec [e-mail]

• Xiaoying Yu [e-mail]

References

1. Villasante-Tezanos A, Kuo Y, Kurinec C, Li Y, Yu X (2024). "A non-parametric approach to predict the recruitment for randomized clinical trials: an example in elderly inpatient settings." BMC medical research methodology, 24, 189. ISSN 1471-2288, https://pubmed.ncbi.nlm.nih.gov/39210285/.

2. Gajewski BJ, Simon SD, Carlson SE (2008). "Predicting accrual in clinical trials with Bayesian posterior predictive distributions." Statistics in medicine, 27, 2328-40. ISSN 0277-6715, https://pubmed.ncbi.nlm.nih.gov/17979152/.

3. Jiang Y, Simon S, Mayo MS, Gajewski BJ (2015). "Modeling and validating Bayesian accrual models on clinical data and simulations using adaptive priors." Statistics in medicine, 34, 613-29. ISSN 1097-0258, https://pubmed.ncbi.nlm.nih.gov/25376910/.

See Also

Useful links:

• https://github.com/imalagaris/RCTRecruit

• Report bugs at https://github.com/imalagaris/RCTRecruit/issues

Packages:

• Liu J, Jiang Y, Wu C, Simon S, Mayo MS, Raghavan R, Gajewski BJ (2023). accrual: Bayesian Accrual Prediction. R package version 1.4, https://CRAN.R-project.org/package=accrual.

Other Links: GetDistance(), GetWeekPredCI(), LoadData(), Time2Nsubjects(), gripsYR1, gripsYR2, gripsYR2Weekly, plot.RCTPredCI()

RCTRecruit documentation built on June 8, 2025, 10:50 a.m.