set_prior_tpr_BrS_NoNest

<code>set_prior_tpr_BrS_NoNest</code> is for for conditional independence models.
We currently also use it for conditional dependence model: subclass TPRs
are independently assigned a beta prior. Ongoing work will enable specifying
priors for the marginal TPR, i.e. TPRs for a disease class, not for the
finer subclass.

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

set_prior_tpr_BrS_NoNest function

<dl><dt>slice</dt>
<dd>The BrS measurement slice under consideration.</dd>
<dt>model_options</dt>
<dd>See <code>nplcm()</code> function.</dd>
<dt>data_nplcm</dt>
<dd>See <code>assign_model()</code> function.</dd></dl>

Arguments

Set true positive rate (TPR) prior ranges for bronze-standard (BrS) data — set_prior_tpr_BrS_NoNest

<dl>

<dt>slice</dt>
<dd>The BrS measurement slice under consideration.</dd>


<dt>model_options</dt>
<dd>See <code>nplcm()</code> function.</dd>


<dt>data_nplcm</dt>
<dd>See <code>assign_model()</code> function.</dd>

</dl>

set_prior_tpr_BrS_NoNest: Set true positive rate (TPR) prior ranges for bronze-standard (BrS) data

Description

Usage

Value

Arguments

See Also