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 LISTSERV Archives SPM Home SPM April 2007

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Re: 2 sample t-test of 2 patients against 16 controls

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Thu, 19 Apr 2007 09:51:10 +0100

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 ```The other day Rik Henson posted this RE testing 1 patient versus a group (1-sample t-test at the second level): post: http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind0704&L=SPM&P=R7490&I=-3 See: http://www.mrc-cbu.cam.ac.uk/~rh01/singlepatient.pdf Hope that helps to solve (part of?) your problem. Most articles describing between-group studies with unequal sample sizes seem to use permutation tests at higher levels. Might be worth a try... best Alle Meije James Rowe wrote: > Your reviewer wonders whether SPM2 can compare 2 vs 16. Clearly it can > do so, since you have done it. The question is whether it is optimal to > do so. There are alternative models, for example: > > 1. one 2 vs 16 2-sample t-test as you have done. > 2. two separate 1 vs 16 2-sample t-test, treating the patients as a case > and replication, with each patient group having n=1. (note that this is > not the same as a one-sample t-test of the differences between your > patient and each control: this should be avoided) > 3. a 1x3 anova, with groups 'controls n=16' vs 'patient n=1' vs 'other > patient n=1', enabling you to look at individual or averaged > differences between patients and controls. > > The choice depends on the inferences you wish to make, the flexibility, > and the assumptions you are prepared to make. For your model, you > should be able to state that the first level models for patients were > similar to controls, in terms of number of scans, covariates and > residual variance, since large differences in the first level (e.g. due > to many more patient errors or worse patient movement) would undermine > the assumptions behind the two-step random effects approach used in > SPM2 (since it is not a true mixed effects model). With your 2 vs 16 > model in SPM 2 you are assuming that the {expected} error variance of > you patients is not different from the control group. This might be > contributing to your reviewer's unease. If you want to avoid many of > these assumptions, you could have a look at SnPM3. Or to allow for > unequal variances you could look at SPM5. ```