Description
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.
README.md
RCTRecruit
Installation
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.
You can install the development version of RCTRecruit from GitHub with:
devtools::install_github("imalagaris/RCTRecruit")
Example
library(RCTRecruit)
LoadData(gripsYR1, ScreenDt, Enrolled)
#>
#> Variables Enrolled and ScreenDt were successfully loaded
Time2Nsubjects()
#> Enrolling 50 subjects requires 148 weeks
#>
#> 2.5% 50% 97.5%
#> 106 148 197
GetDistance(gripsYR2Weekly$enrolled)
#> 2.5% 50% 97.5%
#> 65 104 138
res <- GetWeekPredCI()
res$plot()