data_sim_multi_rec

A simulated real dataset of multivariate recurrent events data with 300 subjects.

datasets

Copula-based regression models for multivariate censored data, including
bivariate right-censored data, bivariate interval-censored data, and right/interval-censored
semi-competing risks data. Currently supports Clayton, Gumbel, Frank, Joe, AMH and
Copula2 copula models. For marginal models, it supports parametric (Weibull, Loglogistic,
Gompertz) and semiparametric (Cox and transformation) models. Includes methods for
convenient prediction and plotting. Also provides a bivariate time-to-event simulation
function and an information ratio-based goodness-of-fit test for copula. Method details
can be found in Sun et.al (2019) Lifetime Data Analysis, Sun et.al (2021) Biostatistics,
Sun et.al (2022) Statistical Methods in Medical Research, Sun et.al (2022) Biometrics, and
Sun et al. (2023+) JRSSC.

Tao Sun

CopulaCenR

Copula-Based Regression Models for Multivariate Censored Data

data_sim_multi_rec function

A list with 300 subjects on the following 2 components.<dl>
 <dt><code>gaptimes</code></dt>
<dd>a data frame with 300 subjects in row and 4 gap times in column</dd> <dt><code>status</code></dt>
<dd>a data frame with 300 subjects in row and 4 statuses in column</dd> 
</dl>

Format

data_sim_multi_rec — data_sim_multi_rec

A list with 300 subjects on the following 2 components.<dl>
 <dt><code>gaptimes</code></dt>
<dd>a data frame with 300 subjects in row and 4 gap times in column</dd>

 <dt><code>status</code></dt>
<dd>a data frame with 300 subjects in row and 4 statuses in column</dd>

 
</dl>

data_sim_multi_rec: data_sim_multi_rec

Description

Usage

Arguments

Format