Imports: caret, data.table, dtw, dynlm, meboot, Quandl, Rfast, rgl,

Imports: caret, data.table, dtw, dynlm, meboot, MESS, Quandl, Rcpp,
RcppParallel, RcppThread, Rfast, rgl, stringr, tseries, zoo

RcppParallel, Rfast, rgl, stringr, tseries, zoo

Imports: caret, data.table, meboot, MESS, quantmod, Rcpp, RcppParallel,

Imports: caret, data.table, dynlm, meboot, MESS, quantmod, Rcpp,
RcppParallel, Rfast, rgl, stringr, xts, zoo

Imports: caret, data.table, meboot, quantmod, Rcpp, RcppParallel,

Package: NNTbiomarker
Type: Package
Title: Calculate Design Parameters for Biomarker Validation Studies
Version: 0.28
Date: 2015-05-05
Author: Roger Day
Maintainer: Roger Day <day01@pitt.edu>
Description: Helps a clinical trial team  discuss
the clinical goals  of a well-defined biomarker with a diagnostic,
staging, prognostic, or predictive purpose.  From this discussion will
come a statistical plan for a (non-randomized) validation trial.
Both prospective and retrospective trials are supported. In a specific
focused discussion, investigators should determine the range of
"discomfort" for the NNT, number needed to treat.  The meaning of
the discomfort range, [NNTlower, NNTupper], is that within this range
most physicians would feel discomfort either in treating or withholding
treatment. A pair of NNT values bracketing that range, NNTpos and NNTneg,
become the targets of the study's design.  If the trial can demonstrate
that a positive biomarker test yields an NNT less than NNTlower,
and that a negative biomarker test yields an NNT less than NNTlower,
then the biomarker may be useful for patients. A highlight of the package
is visualization of a "contra-Bayes" theorem, which produces criteria for
retrospective case-controls studies.
License: GPL-3
Imports: shiny, xtable, stringr
Collate: aaa.R ifVerboseCat.R sesp-pv-NNT.R achievable.se.sp.R
binom.confint.R NNTintervals.R run.R
Suggests: knitr
VignetteBuilder: knitr
Packaged: 2015-05-05 04:07:44 UTC; Roger
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-05-05 16:14:37