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Tip revision: 08b5ab1b4de9d9e30255c8ed47e18c7ecb2faf36 authored by Daniela Dunkler on 09 March 2016, 15:21:00 UTC
version 1.2.1
Tip revision: 08b5ab1
deepvein.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/deepvein.R
\docType{data}
\name{deepvein}
\alias{deepvein}
\title{Deep Vein Thrombosis Study}
\format{The data frame contains observations of 929 individuals and the
    following variables:
 \describe{
     \item{pnr}{ patient number. }
     \item{time}{ time to recurrence of thrombosis or end of study in months. }
     \item{status}{ = 1 recurrence of thrombosis. }
     \item{sex}{ gender. }
     \item{fiimut}{ factor II G20210A mutation. }
     \item{fvleid}{ factor V Leiden mutation. }
     \item{log2ddim}{ log2-transformed D-dimer. }
     \item{bmi}{ body mass index. }
     \item{durther}{ duration of anticoagulation therapy. }
     \item{age}{ age in years. }
     \item{loc}{ location of first thrombosis: pulmonary embolism (PE), distal,
           or proximal deep vein \cr thrombosis. }
}}
\usage{
deepvein
}
\description{
A data frame containing time to recurrence of thrombosis and several potential
prognostic factors measured at baseline for 929 individuals with deep vein
thrombosis or unprovoked pulmonary embolism. 147 events of recurrence were
observed during a median follow-up time of 37.8 months.
}
\note{
The data are a modified and partly simulated version of the data set used
    by Eichinger et al. (2010) and are available under a GPL-2 license.
}
\examples{
 data("deepvein")
 summary(deepvein)
}
\references{
M. Schumacher, G. Basert, H. Bojar,  K. Huebner, M. Olschewski,
    W. Sauerbrei, C. Schmoor, C. Beyerle, R.L.A. Neumann and H.F. Rauschecker
    for the German Breast Cancer Study Group (1994).
    Randomized \eqn{2 \times 2} trial evaluating hormonal treatment
    and the duration of chemotherapy in node-positive breast cancer patients.
    \emph{Journal of Clinical Oncology}, \bold{12}, 2086--2093.\cr
    W. Sauerbrei and P. Royston (1999). Building multivariable prognostic
    and diagnostic models: transformation of the predictors by using
    fractional polynomials. \emph{Journal of the Royal Statistics Society
      Series A}, Volume \bold{162}(1), 71--94.
}
\keyword{datasets}

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