nhanes.demo

datasets

The goal of 'surveynnet' is to extend the functionality of 'nnet',
which already supports survey weights, by enabling it to handle clustered
and stratified data. It achieves this by incorporating design effects
through the use of effective sample sizes as outlined by Chen
and Rust (2017), <doi:10.1093/jssam/smw036>, and performed by
'deffCR' in the package 'PracTools' (Valliant, Dever, and Kreuter (2018),
<doi:10.1007/978-3-319-93632-1>).

Aaron Cohen

surveynnet

Neural Network for Complex Survey Data

Raul Cruz-Cano

nhanes.demo function

<div class="section" id="nhanes-demo">
<h3><code>nhanes.demo</code></h3>
A data frame with 6230 rows and 9 columns:<dl>
<dt>SEQN</dt>
<dd>Respondent sequence number</dd><dt>SDMVPSU</dt>
<dd>Masked variance pseudo-PSU</dd><dt>SDMVSTRA</dt>
<dd>Masked variance pseudo-stratum</dd><dt>WTMEC2YR</dt>
<dd>Full sample 2 year MEC exam weight</dd><dt>BMXHT</dt>
<dd>Standing height (cm)</dd><dt>BMXWT</dt>
<dd>Weight (kg)</dd><dt>BMXBMI</dt>
<dd>Body maxx index (kg/m**2)</dd><dt>BPXSY1</dt>
<dd>Systolic blood pressure</dd><dt>BPXDI1</dt>
<dd>Diastolic blood pressure</dd></dl></div>

Format

Nhanes example — nhanes.demo

<div class='section' id='nhanes-demo'>
<h3><code>nhanes.demo</code></h3>


A data frame with 6230 rows and 9 columns:<dl>
<dt>SEQN</dt>
<dd>Respondent sequence number</dd>

<dt>SDMVPSU</dt>
<dd>Masked variance pseudo-PSU</dd>

<dt>SDMVSTRA</dt>
<dd>Masked variance pseudo-stratum</dd>

<dt>WTMEC2YR</dt>
<dd>Full sample 2 year MEC exam weight</dd>

<dt>BMXHT</dt>
<dd>Standing height (cm)</dd>

<dt>BMXWT</dt>
<dd>Weight (kg)</dd>

<dt>BMXBMI</dt>
<dd>Body maxx index (kg/m**2)</dd>

<dt>BPXSY1</dt>
<dd>Systolic blood pressure</dd>

<dt>BPXDI1</dt>
<dd>Diastolic blood pressure</dd>



</dl>

</div>

nhanes.demo: Nhanes example

Description

Usage

Arguments

Format

`nhanes.demo`