add_meas_BrS_ctrl_Nest_Slice

add likelihood for a BrS measurement slice among controls (conditional independence)

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

add_meas_BrS_ctrl_Nest_Slice function

<dl><dt>s</dt>
<dd>the slice</dd>
<dt>Mobs</dt>
<dd>See <code>data_nplcm</code> described in <code>nplcm()</code></dd>
<dt>cause_list</dt>
<dd>the list of causes in <code>data_nplcm</code> described in <code>nplcm()</code></dd>
<dt>ppd</dt>
<dd>Default is NULL; Set to TRUE for enabling posterior predictive checking.</dd></dl>

Arguments

add likelihood for a BrS measurement slice among controls (conditional independence) — add_meas_BrS_ctrl_Nest_Slice

<dl>

<dt>s</dt>
<dd>the slice</dd>


<dt>Mobs</dt>
<dd>See <code>data_nplcm</code> described in <code>nplcm()</code></dd>


<dt>cause_list</dt>
<dd>the list of causes in <code>data_nplcm</code> described in <code>nplcm()</code></dd>


<dt>ppd</dt>
<dd>Default is NULL; Set to TRUE for enabling posterior predictive checking.</dd>

</dl>

add_meas_BrS_ctrl_Nest_Slice: add likelihood for a BrS measurement slice among controls (conditional independence)

Description

Usage

Value

Arguments

See Also