data_nplcm_noreg

Data set for illustrating regression functionalities

datasets

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

data_nplcm_noreg function

A list containing three items<dl>
<dt>Mobs</dt>
<dd>BrS level measurements: N = 600 (half cases and half controls);
one slice of BrS measurements (6 dimensional, A-F); one slice of SS measurements (2 dimensional,
A and B)</dd><dt>Y</dt>
<dd>case-control status</dd>
</dl>

Format

Simulated dataset that is structured in the format necessary for an nplcm() without regression — data_nplcm_noreg

A list containing three items<dl>
<dt>Mobs</dt>
<dd>BrS level measurements: N = 600 (half cases and half controls);
one slice of BrS measurements (6 dimensional, A-F); one slice of SS measurements (2 dimensional,
A and B)</dd>

<dt>Y</dt>
<dd>case-control status</dd>


</dl>

data_nplcm_noreg: Simulated dataset that is structured in the format necessary for an `nplcm()` without regression

Description

Usage

Arguments

Value

Format