Reply-To: | | [log in to unmask][log in to unmask]> wrote: > I wouldn't think of it as the maximum number of covariates, but the maximum > number of parameters. The reason for this is that if you have one covariate > (say age) and you want to use it in the model, you could: (a) model it as a > single regressor across all groups, or (b) split it by groups into N > regressors/parameters to allow the effect to vary by group. > > Once you decide how your going to model it, I usually go with the rule that > you need at least 5-10 observations per parameter. > > Best Regards, Donald McLaren > ================= > D.G. McLaren, Ph.D. > Postdoctoral Research Fellow, GRECC, Bedford VA > Research Fellow, Department of Neurology, Massachusetts General Hospital and > Harvard Medical School > Office: (773) 406-2464 > ===================== > This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED > HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is > intended only for the use of the individual or entity named above. If the > reader of the e-mail is not the intended recipient or the employee or agent > responsible for delivering it to the intended recipient, you are hereby > notified that you are in possession of confidential and privileged > information. Any unauthorized use, disclosure, copying or the taking of any > action in reliance on the contents of this information is strictly > prohibited and may be unlawful. If you have received this e-mail > unintentionally, please immediately notify the sender via telephone at (773) > 406-2464 or email. > > > > On Fri, Sep 23, 2011 at 10:01 AM, Cyril Pernet <[log in to unmask]> > wrote: >> >> I Gordon >> >> don't know for others but for me as long as your matrix is not rank >> deficient and p<n I don't see any problem ... >> of course the more data points the more likely the effect is likely to be >> 'true' ... now if your covariates are the same across subjects and only want >> to regress this out (without comparisons) then it will fits across your 39 >> subjects .. >> >> Cyril >> >> >> In a full factorial comparison of the functional imaging results of 3 >> groups (N=12,13,14) I would like to include a number of covariates of >> interest. It has been suggested that in normal epidemiological studies a >> rule of thumb suggests 1 covariate for each 20 samples. Even by removing >> covariates that are strongly correlated with each other I have 3 remaining. >> Is there a feeling in the SPM community that this 1/20 ratio is applicable >> here also. >> >> >> >> Thanks, >> >> >> >> Gordon >> >> >> >> Gordon D. Waiter PhD CSci MIPEM CPhys MInstP >> Aberdeen Biomedical Imaging Centre >> Division of Applied Medicine >> University of Aberdeen >> Research MRI Centre >> Lilian Sutton Building >> Foresterhill >> Aberdeen >> AB25 2ZD >> >> Tel: +44 (0)1224 559725 >> Fax: +44 (0)1224 559718 >> >> [log in to unmask] >> www.abdn.ac.uk/ims/imaging >> >> >> >> >> >> >> The University of Aberdeen is a charity registered in Scotland, No >> SC013683. >> >> >> >> The University of Edinburgh is a charitable body, registered in >> Scotland, with registration number SC005336. >> >66_CAK8dPsP1Gf6B6knPQAD153vayXOUg5Ze1X‡fÛ´_ |