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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 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/