tidy.coxphf

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

tidy.coxphf function

<dl><dt>x</dt>
<dd>A `coxphf` object.</dd>
<dt>conf.int</dt>
<dd>Logical indicating whether or not to include 
a confidence interval in the tidied output. Defaults to FALSE.</dd>
<dt>conf.level</dt>
<dd>The confidence level to use for the confidence 
interval if conf.int = TRUE. Must be strictly greater than 0 
and less than 1. Defaults to 0.95, which corresponds to a 
95 percent confidence interval.</dd>
<dt>exponentiate</dt>
<dd>Logical indicating whether or not to display coefficient
estimates on an exponential scale.</dd>
<dt>...</dt>
<dd>Unused, included for generic consistency only.</dd></dl>

Arguments

Tidy a coxphf object — tidy.coxphf

<dl>

<dt>x</dt>
<dd>A `coxphf` object.</dd>


<dt>conf.int</dt>
<dd>Logical indicating whether or not to include 
a confidence interval in the tidied output. Defaults to FALSE.</dd>


<dt>conf.level</dt>
<dd>The confidence level to use for the confidence 
interval if conf.int = TRUE. Must be strictly greater than 0 
and less than 1. Defaults to 0.95, which corresponds to a 
95 percent confidence interval.</dd>


<dt>exponentiate</dt>
<dd>Logical indicating whether or not to display coefficient
estimates on an exponential scale.</dd>


<dt>...</dt>
<dd>Unused, included for generic consistency only.</dd>

</dl>

tidy.coxphf: Tidy a coxphf object

Description

Usage

Value

Arguments