This depends on the analysis you want to do; Maximum Likelihood will
give you unbiased results even under MAR. In this case the more
relevant question is whether the missing data mechanism is MNAR, in
which case ML might give you biased results. Unfortunately you cannot
test MNAR without making, some times very strong, assumptions.
Best,
Dimitris
----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://www.med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Rohit Vishal Kumar" <rohitvk at vsnl.com>
To: <r-help at stat.math.ethz.ch>
Sent: Monday, November 14, 2005 5:40 PM
Subject: [R] Little's Chi Square test for MCAR?
> Hi.
>
> Can anyone point me to any module in R which implements "Little's
> Chi
> Square test" for MCAR.
> The problem is that i have around 60 behavioural variables on a 6
> point
> categorical scale which i need to test for MCAR and MAR. What i can
> make
> out from preliminary analysis is that moderate (0.30 to 0.60)
> correlations may be present in several variable pairs leading me to
> suspect that the data may not be MCAR or MAR. However i need some
> more
> "concrete" proof.
>
> Any help - onlist or offlist - would be greatly appreciated.
>
> Thanks in Advance
>
> Rohit Vishal Kumar
> Ph.D. Student (Calcutta) India
>
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