<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ignorability on Models for missing data</title><link>https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/tags/ignorability/</link><description>Recent content in Ignorability on Models for missing data</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/tags/ignorability/index.xml" rel="self" type="application/rss+xml"/><item><title>Non-ignorable missingness</title><link>https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/posts/non-ignorable-missingness/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://mtaniguchiking.github.io/M4MD-forecast-docs-dev/posts/non-ignorable-missingness/</guid><description>&lt;blockquote&gt;
&lt;p&gt;Statistics is basically a missing data problem!&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;&amp;ndash; Little 2013&lt;/p&gt;
&lt;p&gt;Nearly all samples &amp;ndash; whether by design or by accident &amp;ndash; are incomplete. We very rarely make a complete census of all individuals in a population or all sites on a landscape. Sometimes we don&amp;rsquo;t collect, or can&amp;rsquo;t collect, complete information for individual samples or measures. For instance, we might know an animal was alive when it was last seen, so we know it survived &lt;em&gt;at least&lt;/em&gt; that long, but know nothing about its current status. Or we might have information on the coverage of an invasive species down to a certain patch size, beyond which patches are too small or numerous to survey.&lt;/p&gt;</description></item></channel></rss>