
From  Suzy <[email protected]> 
To  [email protected] 
Subject  Re: st: Re: simple way to create missing data that is "missing atrandom" from a small datset 
Date  Fri, 24 Feb 2006 19:27:20 0500 
Suzy:
You wanted to create missingness according the to a MAR process, in your case the probability of
missingness in the variable bmi should depend on the variable age. So we created the probability
of missingness for each observation. The youngest person in your dataset has a probablity of
missingness of invlogit(8 + .1*28) = .0054863 (type di invlogit(8 + .1*28)) and the oldest
person has a missingness of invlogit(8 + .1*82) = .549834. If the probability of missingness was
constant (or random and unrelated to any of the other variables) than the missingness mechanism
would be missing completely at random MCAR.
HTH,
Maarten
 Suzy <[email protected]> wrote:
I'm not sure what the implications are of the std dev and the max values of p (.549).
between 1/2/2006 and 31/3/2006 I will be
visiting the UCLA, during this time the
best way to reach me is by email
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z214
+31 20 5986715
http://home.fsw.vu.nl/m.buis/

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