hivtest

This dataset concerns the diagnostic accuracy of tests for HIV
infection. Four different tests (<code>A</code>, <code>B</code>,
<code>C</code>, and <code>D</code>) were applied to 428 high-risk patients. The
result from each test is either negative (<code>"neg"</code>) or positive
(<code>"pos"</code>). Yang and Becker (1997) applied latent-class analysis
to these data to estimate the sensitivity and specificity of these
tests in the absence of a gold standard.

 datasets

Extends R's implementation of categorical variables (factors)
to handle coarsened observations; implements log-linear models for
coarsened categorical data, including latent-class models. Detailed
information and examples are provided in the package vignettes.

Joseph Schafer

cvam

Coarsened Variable Modeling

hivtest function

a data frame with 9 rows and 5 variables:
<dl> <dt><code>A</code></dt>
<dd>test result from radioimmunoassay (RIA) utilizing
 recombinant agl21</dd>
 <dt><code>B</code></dt>
<dd>test result from RIA utilizing purified HIV p24</dd>
 <dt><code>C</code></dt>
<dd>test result from RIA utilizing purified HIV
 gpl20</dd>
 <dt><code>D</code></dt>
<dd>test result from enzyme-linked immunosorbent assay</dd>
 <dt><code>COUNT</code></dt>
<dd>frequency; number of patients exhibiting the given 
 pattern of results</dd></dl>

Format

HIV test dataset — hivtest

a data frame with 9 rows and 5 variables:
<dl>

 <dt><code>A</code></dt>
<dd>test result from radioimmunoassay (RIA) utilizing
 recombinant agl21</dd>


 <dt><code>B</code></dt>
<dd>test result from RIA utilizing purified HIV p24</dd>


 <dt><code>C</code></dt>
<dd>test result from RIA utilizing purified HIV
 gpl20</dd>


 <dt><code>D</code></dt>
<dd>test result from enzyme-linked immunosorbent assay</dd>
 

 <dt><code>COUNT</code></dt>
<dd>frequency; number of patients exhibiting the given 
 pattern of results</dd>



</dl>

hivtest: HIV test dataset

Description

Usage

Arguments

Format