 |
 |
Hi Yacila, Please see below: On 2 February 2017 at 12:27, Yacila Isabela Deza Araujo < [log in to unmask]> wrote: > Thanks a lot for your reply Anderson. > > I have another question regarding the use of covariates in within and > between subjects designs in PALM: > > As far as I understood, age and gender do not need to be considered as > covariates because they do not change between the measures, but what about > intervention order? > > Can I create a variable with intervention order to see whether it has > effects in my designs, even when they are not significant between groups? > > And motion measures such as FD? I am working with resting state data and I > cleanes a lot before. There are not differences in FD between groups. > Should I still include the mean FD per subject and intervention? > > My last question is about the place where these nuisance variables should > be: Should I include them in the within or between subjects design? If I > include them in both, my design will be rank deficient, right? > > I am looking forward to your useful comments > > > > Thanks a LOT! > > Yacila > > > > *Von:* FSL - FMRIB's Software Library [mailto:[log in to unmask]] *Im > Auftrag von *Anderson M. Winkler > *Gesendet:* Samstag, 21. Januar 2017 14:54 > *An:* [log in to unmask] > *Betreff:* Re: [FSL] Linear or quadratic effects with permutations > testing? > > > > Hi Yacila, > > > > Please, see below: > > > > > > On 20 January 2017 at 10:06, Yacila Isabela Deza Araujo < > [log in to unmask]> wrote: > > Dear FSL experts, > > (especially Anderson), > > > > I have two groups and three conditions. Anderson already provided me with > a design and contrast template that can be used in Palm. > > My main question is: Is it possible to have linear contrast (or quadratic) > with permutation testing such as randomise or PALM? My conditions are > antagonist, placebo and agonist, so I expected some linear effect more than > a comparison between conditions. > > > > Do you mean a quadratic contrast with these 3 conditions only? With only 3 > values (even if many subjects), this will be prone to overfitting. Testing > the pairwise differences between the 3 conditions, and these between the > groups (as in the design you have) is probably more informative and less > error prone. > > > > If you want something linear as in the order A>B>C, then testing A>C leads > to the same result (and you have this contrast already, so nothing to > change). > > > > > > My second question is whether is valid to investigate main intervention > effects in the total sample, even when I know I have two groups . (It is a > genetic marker, so I also expect differences) > > > > Yes, it's ok, provided there are no group differences. Otherwise the test > is still valid (i.e., "statistically valid") although it may not be > informative. > > > > All the best, > > > > Anderson > > > > > > > > Thanks a lot for the attention! > > > > Yacila > > > > > On 2 February 2017 at 12:27, Yacila Isabela Deza Araujo < [log in to unmask]> wrote: > Thanks a lot for your reply Anderson. > > I have another question regarding the use of covariates in within and > between subjects designs in PALM: > > As far as I understood, age and gender do not need to be considered as > covariates because they do not change between the measures, but what about > intervention order? > > Can I create a variable with intervention order to see whether it has > effects in my designs, even when they are not significant between groups? > > And motion measures such as FD? I am working with resting state data and I > cleanes a lot before. There are not differences in FD between groups. > Should I still include the mean FD per subject and intervention? > > My last question is about the place where these nuisance variables should > be: Should I include them in the within or between subjects design? If I > include them in both, my design will be rank deficient, right? > > I am looking forward to your useful comments > > > > Thanks a LOT! > > Yacila > > > > *Von:* FSL - FMRIB's Software Library [mailto:[log in to unmask]] *Im > Auftrag von *Anderson M. Winkler > *Gesendet:* Samstag, 21. Januar 2017 14:54 > *An:* [log in to unmask] > *Betreff:* Re: [FSL] Linear or quadratic effects with permutations > testing? > > > > Hi Yacila, > > > > Please, see below: > > > > > > On 20 January 2017 at 10:06, Yacila Isabela Deza Araujo < > [log in to unmask]> wrote: > > Dear FSL experts, > > (especially Anderson), > > > > I have two groups and three conditions. Anderson already provided me with > a design and contrast template that can be used in Palm. > > My main question is: Is it possible to have linear contrast (or quadratic) > with permutation testing such as randomise or PALM? My conditions are > antagonist, placebo and agonist, so I expected some linear effect more than > a comparison between conditions. > > > > Do you mean a quadratic contrast with these 3 conditions only? With only 3 > values (even if many subjects), this will be prone to overfitting. Testing > the pairwise differences between the 3 conditions, and these between the > groups (as in the design you have) is probably more informative and less > error prone. > > > > If you want something linear as in the order A>B>C, then testing A>C leads > to the same result (and you have this contrast already, so nothing to > change). > > > > > > My second question is whether is valid to investigate main intervention > effects in the total sample, even when I know I have two groups . (It is a > genetic marker, so I also expect differences) > > > > Yes, it's ok, provided there are no group differences. Otherwise the test > is still valid (i.e., "statistically valid") although it may not be > informative. > > > > All the best, > > > > Anderson > > > > > > > > Thanks a lot for the attention! > > > > Yacila > > > > >