tvc.example

Given a set of (non-time-varying) covariates, creates a simple example
of a matrix of time-varying covariates that can be used as input data
for the mHR2.tvc function.

Nonparametric survival function estimates and semiparametric
regression for the multivariate failure time data with right-censoring.
For nonparametric survival function estimates, the Volterra, Dabrowska,
and Prentice-Cai estimates for bivariate failure time data may be
computed as well as the Dabrowska estimate for the trivariate failure
time data. Bivariate marginal hazard rate regression can be fitted for
the bivariate failure time data. Functions are also provided to compute
(bootstrap) confidence intervals and plot the estimates of the bivariate
survival function. For details, see "The Statistical Analysis of
Multivariate Failure Time Data: A Marginal Modeling Approach", Prentice,
R., Zhao, S. (2019, ISBN: 978-1-4822-5657-4), CRC Press.

Eric Bair

mhazard

Nonparametric and Semiparametric Methods for Multivariate
Failure Time Data

Taylor Petty

Shanshan Zhao

tvc.example function

<dl><dt>Y1, Y2</dt>
<dd>Vectors of event times (continuous).</dd>
<dt>Delta1, Delta2</dt>
<dd>Vectors of censoring indicators (1=event,
0=censored).</dd>
<dt>X</dt>
<dd>Matrix of covariates (continuous or binary).</dd></dl>

Arguments

Creates an example of a matrix of time-varying covariates — tvc.example

<dl>

<dt>Y1, Y2</dt>
<dd>Vectors of event times (continuous).</dd>


<dt>Delta1, Delta2</dt>
<dd>Vectors of censoring indicators (1=event,
0=censored).</dd>


<dt>X</dt>
<dd>Matrix of covariates (continuous or binary).</dd>

</dl>

tvc.example: Creates an example of a matrix of time-varying covariates

Description

Usage

Value

Arguments

Details

See Also

Examples