wald

Obtain Wald chi-squared test statistics and p-values for one or more regression
 coefficients given their variance-covariance matrix.

survival

Implements weighted estimation in Cox regression as proposed by
Schemper, Wakounig and Heinze (Statistics in Medicine, 2009,
<doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and
Heinze (Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>).
Weighted Cox regression provides unbiased average hazard ratio
estimates also in case of non-proportional hazards.
Approximated generalized concordance probability an effect size measure for clear-cut
decisions can be obtained.
The package provides options to estimate time-dependent effects conveniently by
including interactions of covariates with arbitrary functions of time, with or without
making use of the weighting option.

Daniela Dunkler

coxphw

Weighted Estimation in Cox Regression

Georg Heinze

Meinhard Ploner

wald function

<dl> <dt>coeff</dt>
<dd>a vector with regression coefficients.</dd> <dt>cov</dt>
<dd>a variance-covariance matrix.</dd> <dt>index</dt>
<dd>an integer specifying which parameters should be jointly tested. Default is to test
 all parameters given in <code>coeff</code> and <code>cov</code>.</dd> <dt>h0</dt>
<dd>a vector with the same length as <code>coeff</code> stating the null hypothesis for the test.
 Default is 0 for all coefficients.</dd></dl>

Arguments

Author

Wald-Test for Model Coefficients — wald

<dl>

 <dt>coeff</dt>
<dd>a vector with regression coefficients.</dd>

 <dt>cov</dt>
<dd>a variance-covariance matrix.</dd>

 <dt>index</dt>
<dd>an integer specifying which parameters should be jointly tested. Default is to test
 all parameters given in <code>coeff</code> and <code>cov</code>.</dd>

 <dt>h0</dt>
<dd>a vector with the same length as <code>coeff</code> stating the null hypothesis for the test.
 Default is 0 for all coefficients.</dd>

</dl>

wald: Wald-Test for Model Coefficients

Description

Usage

Value

Arguments

Author

Details

See Also