accrual

Participant recruitment for medical research is challenging. Slow accrual leads to delays in research. Accrual monitoring during the process of recruitment is critical. Researchers need reliable tools to manage the accrual rate. We developed a Bayesian method that integrates the researcher's experience with previous trials and data from the current study, providing reliable predictions on accrual rate for clinical studies. For more details and background on these methodologies, see the publications of Byron, Stephen and Susan (2008) doi:10.1002/sim.3128, and Yu et al. (2015) doi:10.1002/sim.6359. In this R package, Bayesian accrual prediction functions are presented, which can be easily used by statisticians and clinical researchers.

Last 30 days

This package has been downloaded 320 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 10 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,190 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Aug 28, 2024 with 68 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.