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From |
"Ploutz-Snyder, Robert (JSC-SK)[USRA]" <robert.ploutz-snyder-1@nasa.gov> |

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

Subject |
RE: st: Unbalanced repeated measures analysis question |

Date |
Wed, 21 Jul 2010 16:37:24 -0500 |

Karin, I feel your pain RE Stata's anova syntax for repeated measures... But I also agree with David that I think your better bet is probably to use -xtmixed- and then apply -margins- for your post-hoc comparisons, given the imbalance issue. You can use -margins- to compare each of the three measures to the gold standard--akin to simple effect contrasts. If you wish to remain in the anova syntax, you might want to check out the user written -anovalator- command, thanks to Phil Ender from UCLA. But from the sounds of your imbalanced design, I would tend to lean more to -xtmixed- with -margins- (BTW--the Phil's website at UCLA has some nice walk-throughs of all of this.) Rob -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Airey, David C Sent: Wednesday, July 21, 2010 4:07 PM To: statalist@hsphsun2.harvard.edu Subject: re: st: Unbalanced repeated measures analysis question . I think when you have comparisons to a gold standard, or all comparisons with one control, that there are specific ANOVA post-hoc tests that perform better than all possible or all pairwise comparisons procedures. There is the complication that you are testing for equivalence, as you say. The Stata command -xtmixed- can do what -anova- can. Sometimes -manova- or -mvtest- is useful with repeated measures too. It is hard to understand how your design is unbalanced without seeing the data cross-tabs, etc. > Hi > > I have data on measuring a biological property for three different > methods plus a gold standard. Different people were trained in each > method (1,2 or 3) and measured the same subjects during different > sessions, together with the gold standard measurement. > > So the data look like > SubjectID MeasurerID MeasurerType Result GoldStandard Diff > 1 1 1 95 99 -4 > 1 2 3 102 99 +3 > 1 3 2 92 99 -7 > ... > 1 10 3 105 99 +6 > 2 1 3 98 100 -2 > ... > > Sometimes patients would be called in to see the consultant and so > missed for a particular measurer, but otherwise all the measurers > would measure all the patients seen in a particular session. Different > sets of measurers (but all trained by methods 1,2 or 3) were used on > each session (individual measurers 1-10 on session 1, 11-20 on session > 2 etc). > > The gold standard measurements on each session are roughly normally > distributed, as are the differences from the gold standard. We are > interested in the accuracy of each of the three methods. > > Is it OK to do some sort of repeated measures ANOVA here, with an > unbalanced design? If it is what would be the syntax (Stata 10)? Sorry > to sound pathetic but I just can't get the anova command with the > repeated option to work here. > > Is there a better measure to use than the difference to reflect the > fact that we are interested in a comparison with a gold standard? > > Thankyou > Karin * * 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/ * * 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/

**Follow-Ups**:**Re: st: Unbalanced repeated measures analysis question***From:*K Jensen <k.x.jensen@gmail.com>

**References**:**re: st: Unbalanced repeated measures analysis question***From:*"Airey, David C" <david.airey@Vanderbilt.Edu>

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