59 lines (58 with data), 1.8 kB

Package: eventPrediction
Type: Package
Title: Event Prediction in Clinical Trials with Time-to-Event Outcomes
Version: 2.4.1
Date: 2015-11-24
Author: Daniel Dalevi and Nik Burkoff with contributions from Helen Mann, Paul
    Metcalfe and David Ruau
Maintainer: Daniel Dalevi <daniel.dalevi@astrazeneca.com>
Description: 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.
License: GPL (>=2)
Depends:
    ggplot2,
    survival,
    methods,
    scales,
    R (>= 2.10)
Imports:
    mvtnorm,
    stats
Suggests:
    knitr,
    testthat
VignetteBuilder: knitr
Collate:
    'timeInternal.R'
    'simQOutput.R'
    'common.R'
    'fromDataInternal.R'
    'eventPrediction_package.R'
    'fromDataSimParam.R'
    'eventData.R'
    'accrual.R'
    'ctrlSpec.R'
    'singleSimDetails.R'
    'longlagSettings.R'
    'dataResults.R'
    'displayOptions.R'
    'eventDataDiagnostic.R'
    'fromDataSimInternal.R'
    'eventModel.R'
    'fromParameterInternal.R'
    'sfn.R'
    'lag.R'
    'study.R'
    'results.R'
    'fromParameterPlot.R'
    'simulate.R'
    'study_constructors.R'
    'summaryText.R'
    'system_tests.R'
RoxygenNote: 5.0.1