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Date:         Wed, 27 Feb 2008 05:01:49 -0800
Reply-To:     Amw5Gster <amw5gster@GMAIL.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Amw5Gster <amw5gster@GMAIL.COM>
Subject:      Re: Missing data that means something
Comments: To:
Content-Type: text/plain; charset=ISO-8859-1

Thanks, all (and those who emailed me separately). Good stuff that I hadn't wholly considered. I think my approach is going to be a bit of a blend of these suggestions. I'm going to create binary flags for those variables where a missing indicates NULL or n/a. And cluster those separately, then cluster the clusters on those variables that are common amongst the entire population. For example, everyone who purchased product A, cluster the observations only on those variables that pertain to purchase of product A repeat for product B, C, etc. Can do the same thing for presence of children/children ages Then use the cluster identifiers for all these segments as a nominal input variable into the master clustering

Haven't fully thought it through, but it sounded good when I first thought of it (like so many of my plans....)

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