surdata

A simulated dataset to test functions for imputation compatible with cox model.

Similarly to package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi:10.1002/9781119942283>.
Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.

Matteo Quartagno

jomo

Multilevel Joint Modelling Multiple Imputation

surdata function

A data frame with 500 observations on the following 5 variables.<dl>
 <dt><code>measure</code></dt>
<dd>A numeric variable with some measure of interest (unspecified). This is partially observed.</dd> <dt><code>sex</code></dt>
<dd>A binary variable with gender indicator. Partially observed.</dd> <dt><code>id</code></dt>
<dd>The id for individuals within each city.</dd> <dt><code>time</code></dt>
<dd>Time to event (death or censoring).</dd> <dt><code>status</code></dt>
<dd>Binary variables, which takes value 0 for censored observations and 1 for deaths/events.</dd> 
</dl>

Format

A simulated dataset with survival data — surdata

A data frame with 500 observations on the following 5 variables.<dl>
 <dt><code>measure</code></dt>
<dd>A numeric variable with some measure of interest (unspecified). This is partially observed.</dd>

 <dt><code>sex</code></dt>
<dd>A binary variable with gender indicator. Partially observed.</dd>

 <dt><code>id</code></dt>
<dd>The id for individuals within each city.</dd>

 <dt><code>time</code></dt>
<dd>Time to event (death or censoring).</dd>

 <dt><code>status</code></dt>
<dd>Binary variables, which takes value 0 for censored observations and 1 for deaths/events.</dd>

 
</dl>

surdata: A simulated dataset with survival data

Description

Usage

Arguments

Format

Details