Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Joseph Coveney" <jcoveney@bigplanet.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: RM ANOVA, was SPSS vs. Stata |

Date |
Tue, 3 Aug 2010 10:37:14 +0900 |

Robert Ploutz-Snyder wrote: " Doesn't SPSS wrap GLM for its RM-ANOVA routines?" Yes--but with repeated measures designs, SPSS (and SAS, Systat, and BMDP in the old days) use listwise elimination. Stata does not (is there an option in Stata's anova, repeated() code to do so??) " Can you post an example of what you are talking about, re listwise elimination? I don't have SPSS." [example omitted] Of course, with a sample size this tiny, we wouldn't trust either analysis. The point is that the prevailing wisdom for fixed-factorial repeated measures ANOVA is to use listwise elimination, and Stata doesn't do this. (And you get the same Stata results if you use the anova command without the repeated option but instead define the error terms manually--a process that is itself painful enough to avoid entirely if you have 2 or 3 factors, especially if more than 1 are repeated.) I appreciate that it is possible to "manually" tell Stata to ignore listwise those subjects who are missing any data... However this can get more complicated when there is more than 1 repeated measures factor (example, drugs a b c, measured pre and post). And... exactly what is Stata's analysis "by default" anyway? I could not write that up as a standard repeated measures ANOVA because it isn't that. To me, a straightforward improvement to Stata's -anova- would be to force it to ignore any subjects who are missing any repeated measures observations. That alone would be useful. -------------------------------------------------------------------------------- There isn't an option in -anova , repeated()- to use listwise elimination to my knowledge. I believe that Stata's analysis by default is fixed-effects panel-data analysis. Compare the results between -anova- and -xtreg , fe- with your example to see this. You can use -fill- and then -drop if missing()- in order to help simplify manual listwise elimination. Joseph Coveney P.S. The example that you gave is probably not the best one to make your case. Unbalanced repeated-measures factors result in problematic bias with repeated-measures ANOVA when one factor is nested under another (i.e., is considered a random effect and the analysis depends upon estimating its variance), such as -anova score group / patient|group time group*time, repeated(time)-. Although the groups don't need equal numbers of patients (the dataset can be unbalanced in that sense), patients with missing observations across time will cause problems in estimating the patient variance component, which is needed for testing group effects. For the example that you gave, I would want to keep all available data (Stata's default) and would be peeved with SPSS's automatically deciding on my behalf to perform listwise elimination. * * 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/

**References**:**st: re: RM ANOVA, was SPSS vs. Stata***From:*"Airey, David C" <david.airey@Vanderbilt.Edu>

**st: RE: re: RM ANOVA, was SPSS vs. Stata***From:*"Ploutz-Snyder, Robert (JSC-SK)[USRA]" <robert.ploutz-snyder-1@nasa.gov>

- Prev by Date:
**Re: Re: st: Multiple imputation is increasing the sample size** - Next by Date:
**st: creative cover on An Introduction to Stata for Health Researchers, 3rd Edition** - Previous by thread:
**st: RE: re: RM ANOVA, was SPSS vs. Stata** - Next by thread:
**st: Pairing predictors in tuples.** - Index(es):