Imat2cat

Convert a matrix of binary indicators to categorical variables

Provides functions to specify, fit and visualize
nested partially-latent class models (
Wu, Deloria-Knoll, Hammitt, and Zeger (2016) <doi:10.1111/rssc.12101>;
Wu, Deloria-Knoll, and Zeger (2017) <doi:10.1093/biostatistics/kxw037>;
Wu and Chen (2021) <doi:10.1002/sim.8804>) for
inference of population disease etiology and individual diagnosis. In the motivating
Pneumonia Etiology Research for Child Health (PERCH) study, because both quantities
of interest sum to one hundred percent, the PERCH scientists frequently refer to
them as population etiology pie and individual etiology pie, hence the name of the package.

Zhenke Wu

baker

"Nested Partially Latent Class Models"

Scott Zeger

John Muschelli

Irena Chen

Imat2cat function

<dl><dt>binary_mat</dt>
<dd>The matrix of binary indicators. Rows for subjects, columns for pathogens in the <code>"pathogen.list"</code></dd>
<dt>cause_list</dt>
<dd>The list of causes</dd>
<dt>pathogen_list</dt>
<dd>The complete list of pathogen names</dd></dl>

Arguments

Convert a matrix of binary indicators to categorical variables — Imat2cat

<dl>

<dt>binary_mat</dt>
<dd>The matrix of binary indicators. Rows for subjects, columns for pathogens in the <code>"pathogen.list"</code></dd>


<dt>cause_list</dt>
<dd>The list of causes</dd>


<dt>pathogen_list</dt>
<dd>The complete list of pathogen names</dd>

</dl>

Imat2cat: Convert a matrix of binary indicators to categorical variables

Description

Usage

Value

Arguments

Examples