flag.ex01

Anthropometric data from a SMART survey in Sudan.

datasets

An implementation of the National Information Platforms for
Nutrition or NiPN's analytic methods for assessing quality of anthropometric
datasets that include measurements of weight, height or length, middle upper
arm circumference, sex and age. The focus is on anthropometric status but
many of the presented methods could be applied to other variables.

Ernest Guevarra

nipnTK

National Information Platforms for Nutrition Anthropometric Data
Toolkit

Mark Myatt

flag.ex01 function

A data frame with 786 observations and 11 variables<table class="table">
<tr><td>Variable</td><td>Description</td></tr>
<tr><td>psu</td><td>Primary sampling unit</td></tr>
<tr><td>child</td><td>Child ID</td></tr>
<tr><td>age</td><td>Age (months)</td></tr>
<tr><td>sex</td><td>Gender (1 = Male / 2 = Female)</td></tr>
<tr><td>weight</td><td>Weight (kg)</td></tr>
<tr><td>height</td><td>Height (cm)</td></tr>
<tr><td>muac</td><td>Mid-upper arm circumference (mm)</td></tr>
<tr><td>oedema</td><td>Presence or absence of oedema</td></tr>
<tr><td>haz</td><td>Height-for-age z-score</td></tr>
<tr><td>waz</td><td>Weight-for-age z-score</td></tr>
<tr><td>whz</td><td>Weight-for-height z-score</td></tr>
</table>

Format

Example dataset for identifying outliers using flags — flag.ex01

A data frame with 786 observations and 11 variables<table class='table'>
<tr><td>Variable</td><td>Description</td></tr>
<tr><td>psu</td><td>Primary sampling unit</td></tr>
<tr><td>child</td><td>Child ID</td></tr>
<tr><td>age</td><td>Age (months)</td></tr>
<tr><td>sex</td><td>Gender (1 = Male / 2 = Female)</td></tr>
<tr><td>weight</td><td>Weight (kg)</td></tr>
<tr><td>height</td><td>Height (cm)</td></tr>
<tr><td>muac</td><td>Mid-upper arm circumference (mm)</td></tr>
<tr><td>oedema</td><td>Presence or absence of oedema</td></tr>
<tr><td>haz</td><td>Height-for-age z-score</td></tr>
<tr><td>waz</td><td>Weight-for-age z-score</td></tr>
<tr><td>whz</td><td>Weight-for-height z-score</td></tr>
</table>

Variable	Description
psu	Primary sampling unit
child	Child ID
age	Age (months)
sex	Gender (1 = Male / 2 = Female)
weight	Weight (kg)
height	Height (cm)
muac	Mid-upper arm circumference (mm)
oedema	Presence or absence of oedema
haz	Height-for-age z-score
waz	Weight-for-age z-score
whz	Weight-for-height z-score

flag.ex01: Example dataset for identifying outliers using flags

Description

Usage

Arguments

Format