My thanks to all who responded to my query.
On Feb 27, 2005, at 8:58 AM, Alan Zaslavsky wrote: > There are a couple of ways of looking at this, and it pays to think a > bit beyond the definitions to the analyses that would be required. I > agree that your first scenario is MCAR. In the second scenario, > missingness is clustered by months. An analysis that ignored the > clustering (by ignoring the dependence of missingness on the month > labels) would be likely to be wrong, esepcially if you were interested > in inference beyond the sampled months. However we sometimes make a > distinction between design variables (those known before data are > collected) and data; with that distinction, the month labels are > design variables but the missingness is independent of both observed > and unobserved data values. > > In any case the bottom line is that an analysis that didn't take into > account the fact that data are only collected in some months would > most likely be incorrect in some way. > >> Date: Fri, 25 Feb 2005 15:39:12 -0700 >> From: Melissa Roberts <[email protected]> >> Subject: [Impute] MCAR & MAR assessment >> I have monthly event data that covers many individuals over several >> years. For discussion purposes say I have 100 people and 36 months >> of data for them, so I have 3600 observations. Events are not >> consistent from month to month, but there is some consistency in >> events across months at an individual level. >> If I randomly sample from those 3600 observations - for example take >> 20% using a uniform random number generator - then I am confident is >> saying the unsampled data can be characterized as MCAR - missing >> completely at random. The mechanism for being unsampled has nothing >> to do with variables in the data. >> NOW, another sampling method is to randomly sample the MONTHS in the >> dataset. I take a 20% sample of the months (producing 7 months), and >> take all the people represented in those months (100 each month), for >> a total of 700 observations. >> Can I assert that this second sample is also MCAR? The mechanism for >> not being sampled is based solely on a random number generator. >> Is the fact that some months are not represented a problem? Would it >> be just MAR because the nature of the events in those unsampled >> months could be different than those sampled months? Would >> characterizing it as MAR be a problem also? > > > > _______________________________________________ > Impute mailing list > [email protected] > http://lists.utsouthwestern.edu/mailman/listinfo/impute > _________________________________ Melissa H. Roberts Energy, Economic and Environmental Consultants E3c, Inc. 5600 Wyoming Blvd. NE, Suite 225 Albuquerque, NM 87109 (505) 822-9760 (voice) (505) 822-9762 (fax) [email protected] __________________________________
