ex_cc

A dataset containing simulated case cohort data, where the sub-cohort was a 10% random sample of the full cohort.

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_cc function

A data frame with 1571 rows and 7 variables:<dl>
 <dt>t</dt>
<dd>Time to event or censoring</dd> <dt>d</dt>
<dd>Indicator of whether event 1 occurred (d=1), or not (d=0)</dd> <dt>x</dt>
<dd>Partially observed continuous covariate</dd> <dt>z</dt>
<dd>Fully observed covariate</dd> <dt>in.subco</dt>
<dd>A binary indicator of whether the subject is in the sub-cohort</dd> <dt>id</dt>
<dd>An id variable</dd> <dt>entertime</dt>
<dd>The entry time variable to be used in the analysis</dd>
</dl>

Format

Simulated case cohort data — ex_cc

A data frame with 1571 rows and 7 variables:<dl>
 <dt>t</dt>
<dd>Time to event or censoring</dd>

 <dt>d</dt>
<dd>Indicator of whether event 1 occurred (d=1), or not (d=0)</dd>

 <dt>x</dt>
<dd>Partially observed continuous covariate</dd>

 <dt>z</dt>
<dd>Fully observed covariate</dd>

 <dt>in.subco</dt>
<dd>A binary indicator of whether the subject is in the sub-cohort</dd>

 <dt>id</dt>
<dd>An id variable</dd>

 <dt>entertime</dt>
<dd>The entry time variable to be used in the analysis</dd>


</dl>

ex_cc: Simulated case cohort data

Description

Usage

Arguments

Format