breast

Provides the breast cancer data set as used by Heinze &amp; Schemper, 2001. 
The data sets contains information on 100 breast cancer patients, including:
survival time, survival status, Tumor stage, Nodal status, Grading, Cathepsin-D tumorexpression

datasets

Implements Firth's penalized maximum likelihood bias reduction method  for Cox regression
which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see
Heinze and Schemper (2001) and Heinze and Dunkler (2008).
The program fits profile penalized likelihood confidence intervals which were proved to outperform
Wald confidence intervals.

Georg Heinze

coxphf

Cox Regression with Firth's Penalized Likelihood

Meinhard Ploner

Lena Jiricka

Gregor Steiner

breast function

A data frame with 100 observations on the following 6 variables.<dl>
 <dt><code>T</code></dt>
<dd>a numeric vector</dd> <dt><code>N</code></dt>
<dd>a numeric vector</dd> <dt><code>G</code></dt>
<dd>a numeric vector</dd> <dt><code>CD</code></dt>
<dd>a numeric vector</dd> <dt><code>TIME</code></dt>
<dd>a numeric vector</dd> <dt><code>CENS</code></dt>
<dd>a numeric vector</dd>
</dl>

Format

Breast Cancer Data Set — breast

A data frame with 100 observations on the following 6 variables.<dl>
 <dt><code>T</code></dt>
<dd>a numeric vector</dd>

 <dt><code>N</code></dt>
<dd>a numeric vector</dd>

 <dt><code>G</code></dt>
<dd>a numeric vector</dd>

 <dt><code>CD</code></dt>
<dd>a numeric vector</dd>

 <dt><code>TIME</code></dt>
<dd>a numeric vector</dd>

 <dt><code>CENS</code></dt>
<dd>a numeric vector</dd>


</dl>

breast: Breast Cancer Data Set

Description

Usage

Arguments

Format

References