PLAC_TI

C++ Function for Solving the PLAC Estimator.
(with time-invariant convariates only)

A semi-parametric estimation method for the Cox model
with left-truncated data using augmented information
from the marginal of truncation times.

Fan Wu

plac

A Pairwise Likelihood Augmented Cox Estimator for Left-Truncated
Data

PLAC_TI function

<dl><dt>Z</dt>
<dd>matrix for all the covariates history.</dd>
<dt>X</dt>
<dd>the response matrix (As, Xs, Ds).</dd>
<dt>W</dt>
<dd>the ordered observed event times.</dd>
<dt>Ind1</dt>
<dd>risk-set indicators.</dd>
<dt>Ind2</dt>
<dd>truncation pair indicators.</dd>
<dt>Dn</dt>
<dd>number of ties at each observed event time.</dd>
<dt>b</dt>
<dd>initial values of the regression coefficients.</dd>
<dt>h</dt>
<dd>initial values of the baseline hazard function.</dd>
<dt>K</dt>
<dd>maximal iteration number, the default is <code>K = 100</code>.</dd></dl>

Arguments

C++ Function for Solving the PLAC Estimator.
(with time-invariant convariates only) — PLAC_TI

<dl>

<dt>Z</dt>
<dd>matrix for all the covariates history.</dd>


<dt>X</dt>
<dd>the response matrix (As, Xs, Ds).</dd>


<dt>W</dt>
<dd>the ordered observed event times.</dd>


<dt>Ind1</dt>
<dd>risk-set indicators.</dd>


<dt>Ind2</dt>
<dd>truncation pair indicators.</dd>


<dt>Dn</dt>
<dd>number of ties at each observed event time.</dd>


<dt>b</dt>
<dd>initial values of the regression coefficients.</dd>


<dt>h</dt>
<dd>initial values of the baseline hazard function.</dd>


<dt>K</dt>
<dd>maximal iteration number, the default is <code>K = 100</code>.</dd>

</dl>

PLAC_TI: C++ Function for Solving the PLAC Estimator. (with time-invariant convariates only)

Description

Usage

Value

Arguments