ex_poisson

A dataset containing simulated data where the count outcome depends on two
covariates, x and z, with missing values in x. The substantive model is
Poisson regression.

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_poisson function

A data frame with 1000 rows and 3 variables:<dl>
 <dt>y</dt>
<dd>Count outcome</dd> <dt>z</dt>
<dd>Fully observed covariate, with linear effect on outcome</dd> <dt>x</dt>
<dd>Partially observed normally distributed covariate, with linear effect on outcome</dd>
</dl>

Format

Simulated example data with count outcome, modelled using Poisson regression — ex_poisson

A data frame with 1000 rows and 3 variables:<dl>
 <dt>y</dt>
<dd>Count outcome</dd>

 <dt>z</dt>
<dd>Fully observed covariate, with linear effect on outcome</dd>

 <dt>x</dt>
<dd>Partially observed normally distributed covariate, with linear effect on outcome</dd>


</dl>

ex_poisson: Simulated example data with count outcome, modelled using Poisson regression

Description

Usage

Arguments

Format