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Re: st: Repeated Measures ANOVA and Missing Values


From   Philip Ender <ender97@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Repeated Measures ANOVA and Missing Values
Date   Sun, 16 Oct 2011 16:27:37 -0700

I'm trying to run a oneway repeated measures ANOVA (the variable is =
session, with three levels).  I have organized my data in long format, =
with one column for subject ID, one column for session number and one =
column for the dependent variable.  Here is a listing of part of my data =
file:
...
There are obviously several cases that are missing observations at =
session 2 or session 3.  Does wsanova or Stata's anova command =
automatically drop cases with missing values at any of the three =
sessions?  My first pass with the analysis seems to suggest it does not.

What is the best way to deal with these missing values (either deleting =
cases with missing values or telling wsanova or anova to ignore them in =
the analysis)?
-------------------------------
John,

You are correct, -wsanova- does not drop cases that have missing
observations.  If
want complete case analysis you will have to drop observations manually.

However, if you want to use all of the observations I would recommend
-xtmixed-.  It
would look something like this in Stata 12:
xtmixed DV i.session || ID:, reml
testparm i.session

If you have lots of subjects you can use the chi-square value as is.
If your sample is on
the small size, you can rescale the chi-square to F by dividing it by
its df (in your case 2).
You can use the residual df from the -wsanova- as denominator df.  The
-Ftail- function
will get you the p-value.

This approach is not universally approved depending upon what
discipline you come from.
My Chicago Stata Users Group presentation on this topic can be found at
http://www.stata.com/meeting/chicago11/materials/chi11_ender.pdf

-- 
Phil Ender
UCLA Statistical Consulting Group
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