ex_dtsam

A dataset containing simulated discrete time survival data.

datasets

Implements multiple imputation of missing covariates by
Substantive Model Compatible Fully Conditional Specification.
This is a modification of the popular FCS/chained equations
multiple imputation approach, and allows imputation of missing
covariate values from models which are compatible with the user
specified substantive model.

Jonathan Bartlett

smcfcs

Multiple Imputation of Covariates by Substantive Model
Compatible Fully Conditional Specification

Ruth Keogh

Edouard F. Bonneville

Claus Thorn Ekstrøm

ex_dtsam function

A data frame with 1000 rows and 8 variables:<dl>
 <dt>x1</dt>
<dd>A binary variable with missing values</dd> <dt>x2</dt>
<dd>A fully observed continuous variable</dd> <dt>failtime</dt>
<dd>The discrete failure/censoring time</dd> <dt>d</dt>
<dd>Indicator of failure (=1) or censoring (=0)</dd>
</dl>

Format

Simulated discrete time survival data set — ex_dtsam

A data frame with 1000 rows and 8 variables:<dl>
 <dt>x1</dt>
<dd>A binary variable with missing values</dd>

 <dt>x2</dt>
<dd>A fully observed continuous variable</dd>

 <dt>failtime</dt>
<dd>The discrete failure/censoring time</dd>

 <dt>d</dt>
<dd>Indicator of failure (=1) or censoring (=0)</dd>


</dl>

ex_dtsam: Simulated discrete time survival data set

Description

Usage

Arguments

Format