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Re: st: Repeated Measures ANOVA and Missing Values

From   Philip Ender <>
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 =
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)?

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

Phil Ender
UCLA Statistical Consulting Group
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