{simaerep} was originally developed to detect sites that are under-reporting Adverse Events (AE) in clinical trials using a nonparametric bootstrap algorithm. With the release of the most current version v0.5.0 {simaerep} can also be used to detect over-reporting. With this [...]
IMPALA's newest publication has been released in the April 2024 version of Therapeutic Innovation & Regulatory Science. In this paper, IMPALA member representatives validate the open-source R package {simaerep}, which was developed to facilitate rapid, comprehensive, and near-real-time detection of [...]
Register now! https://ieee-isto.webex.com/weblink/register/r6bf252e9bccdc8a1607f9752234b192c Join IMPALA on Monday, May 6th 10am-11am ET/ 4pm-5pm CET for it's webinar "Identifying Anomalies in Clinical Trial Data with CTAS (Clinical Trial Anomaly Spotter.)" In this interactive webinar, the developers of CTAS - a powerful tool [...]
IMPALA is partnering with Momentum Events to host the Clinical Data Analytics Virtual Education and Networking Event on leveraging data to drive decisions that streamline processes and optimize efficiencies in clinical operations. The virtual event will be on February 15, [...]
IMPALA Consortium is pleased to announce the release of its newest open-source R Package, the Clinical Trial Anomaly Spotter (CTAS.) CTAS is a powerful tool for Central Statistical Monitoring that identifies outliers and anomalies efficiently and accurately in clinical trial [...]
