parse_nplcm_reg

parse regression components (either false positive rate or etiology regression)
for fitting npLCM; Only use this when formula is not <code>NULL</code>.

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

parse_nplcm_reg function

<dl><dt>form</dt>
<dd>regression formula</dd>
<dt>data_nplcm</dt>
<dd>data object for <code>nplcm()</code>; may contain covariates X;
must have case-control status Y.</dd>
<dt>silent</dt>
<dd>Default is <code>TRUE</code> for no message about covariates;
<code>FALSE</code> otherwise.</dd></dl>

Arguments

parse regression components (either false positive rate or etiology regression)
for fitting npLCM; Only use this when formula is not NULL. — parse_nplcm_reg

<dl>

<dt>form</dt>
<dd>regression formula</dd>


<dt>data_nplcm</dt>
<dd>data object for <code>nplcm()</code>; may contain covariates X;
must have case-control status Y.</dd>


<dt>silent</dt>
<dd>Default is <code>TRUE</code> for no message about covariates;
<code>FALSE</code> otherwise.</dd>

</dl>

parse regression components (either false positive rate or etiology regression)
for fitting npLCM; Only use this when formula is not <code>NULL</code>.

parse_nplcm_reg: parse regression components (either false positive rate or etiology regression) for fitting npLCM; Only use this when formula is not `NULL`.

Description

Usage

Value

Arguments