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| From | K Jensen <k.x.jensen@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: Unbalanced repeated measures analysis question |
| Date | Thu, 22 Jul 2010 16:50:09 +0100 |
I would like to just try to play around with it before I commit to a book. The repeated measure terms (MeasurerID, SubjectID) are not nested. I think I would like to model with these as random effects and measurer type as a fixed effect, having multiple measurements for each and not being interested in individual subjects or measurers. xi:xtmixed Result i.MeasurerType || SubjectID: || MeasurerID: is *not* right for this, but I can't see any mention of non-nested models in the help. Thankyou Karin On 22 July 2010 14:35, Ploutz-Snyder, Robert (JSC-SK)[USRA] <robert.ploutz-snyder-1@nasa.gov> wrote: > Karin, > > You could define your model the way you suggested, yes, however > mixed models can be specified a number of different ways > depending on your research goals and how you want to consider the > nesting of your repeated measures factors (i.e. random terms). > > There are a number of excellent books on this type of analysis, > going by names including mixed-effects modeling, mixed modeling, > higher level modeling (HLM), multi-level modeling (MLM) and > probably a few other terms... If you are interested in a more > Applied book that uses Stata in particular, Rabe-Hesketh and > Skrondal put together a nice one book called Multilevel and > Longitudinal Modeling Using Stata. I think you might do well to > take a course in MLM if you can to at least wrap your brain > around the theory. But if you want to jump right in then a book > like this one could get you going in the right direction. > > Rob > > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of K Jensen > Sent: Thursday, July 22, 2010 5:33 AM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Unbalanced repeated measures analysis question > > Thanks to Robert and David for your helpful comments. Sorry to sound > stupid here but mixed models are entirely new to me. I have been > reading up on them. > > I have the variables outlined below: > SubjectID MeasurerID MeasurerType Result GoldStandard > where MeasurerID is always a certain MeasurerType (1-3) > > SubjectID and MeasurerID should be random effects and MeasurerType > fixed? How would you specify that in the xtmixed syntax? I am > confused about having two grouping variables for the random effects. > > Karin > > On 21 July 2010 22:37, Ploutz-Snyder, Robert (JSC-SK)[USRA] > <robert.ploutz-snyder-1@nasa.gov> wrote: >> 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/ > * * 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/