get_fitted_mean_no_nested

get model fitted mean for conditional independence model

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

get_fitted_mean_no_nested function

<dl><dt>slice</dt>
<dd>the slice of BrS data that are modeled</dd>
<dt>res_nplcm</dt>
<dd>matrix of MCMC samples</dd>
<dt>model_options</dt>
<dd>see <code>nplcm()</code></dd>
<dt>data_nplcm</dt>
<dd>see <code>nplcm()</code></dd>
<dt>clean_options</dt>
<dd>see <code>clean_perch_data()</code></dd></dl>

Arguments

get model fitted mean for conditional independence model — get_fitted_mean_no_nested

<dl>

<dt>slice</dt>
<dd>the slice of BrS data that are modeled</dd>


<dt>res_nplcm</dt>
<dd>matrix of MCMC samples</dd>


<dt>model_options</dt>
<dd>see <code>nplcm()</code></dd>


<dt>data_nplcm</dt>
<dd>see <code>nplcm()</code></dd>


<dt>clean_options</dt>
<dd>see <code>clean_perch_data()</code></dd>

</dl>

get_fitted_mean_no_nested: get model fitted mean for conditional independence model

Description

Usage

Value

Arguments