scientific-computing-solutions/eventPrediction: Event Prediction in Clinical Trials with Time-to-Event Outcomes

There are two main parts of this package: 1) Predictions about the required number of events in a 2-arm survival study from a fixed set of parameters, 2) Predictions about the time when reaching a target level of events from accumulated data analysed at an interim in a blinded survival study. 1) uses an exponential or Weibull model for survival and accrual according to a fixed non linear function. 2) by default uses a Weibull model for survival and either a Poisson process or a non-linear function for accrual. This package is based on earlier work by Christophe Delong and Sally Hollis.

Getting started

Package details

AuthorDaniel Dalevi and Nik Burkoff with contributions from Helen Mann, Paul Metcalfe and David Ruau
MaintainerDaniel Dalevi <daniel.dalevi@astrazeneca.com>
LicenseGPL (>=2)
Version2.4.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("scientific-computing-solutions/eventPrediction")
scientific-computing-solutions/eventPrediction documentation built on May 29, 2019, 3:44 p.m.