Dear Jerome One possible solution to your problem is to realize, that not every condition needs to be specified in every subject. Thus, you can set up a flexible factorial model using two factors: Subject and condition. Usually, you would specify unequal variance but independence between subjects and unequal variance and non-independence for conditions. As main-effects & interactions, only specify the main effect for the condition-factor. For subjects in Group 1, you then specify the scans as belonging to condition 1-3, for subjects in Group 2 as belonging to conditions 4-6. In the ensuing design (with 6 cells corresponding to the three conditions in the two groups) you can then test for all main effects and interactions. best Simon ________________________________________ Von: SPM (Statistical Parametric Mapping) [[log in to unmask]]" im Auftrag von "Jérôme Redouté [[log in to unmask]] Gesendet: Donnerstag, 10. Mai 2012 12:21 An: [log in to unmask] Betreff: Re: [SPM] Between-groups comparisons Le 08/05/2012 20:42, MCLAREN, Donald a écrit : > You stated that you have a contrast between two conditions. This > implied that you have one measurement per subject. Thus, the > two-sample t-test would be appropriate. > > If you mean that you have two conditions that you want to compare > between groups, then you have 2 measures per subject. Thus, the > flexible factorial would be appropriate. Remember that you will only > be able to compare the two conditions or the group*condition > interaction. The effect of group is invalid. > Dear SPMers, We are facing a similar problem as we have to analyse an O15-H20 PET study with the following specifications: 2 groups: ON medication / OFF medication 3 conditions: Task1 / Task2 / Control (2 or 3 repetition by task) We defined our design matrix with a flexible factorial design as follows Factor 1: subjects Factor 2: Group Factor 3: Tasks Our main questions here, are to compare: Task 1 vs Control between ON & OFF groups Task 2 vs Control between ON & OFF groups there are different options concerning the effects to include in the Matrix Main effect of subject (Factor 1) Main effect of Group ? Main effect of Tasks ? interaction Group x Task (Factor 2 x Factor 3) In the case of interaction Group x Task, the contrast weights we need to define are different whereas the main effects are modelized or not... More specifically, if Main Effects are included, it's impossible to test only the interaction term: the contrast manager seems to wait for weights in the Main effects columns too. Any suggestions to help us analyze these data are welcome... Thanks for your help J.R -- ================================================================== Jérôme Redouté Ph.D. - Ingénieur de Recherche - Université Claude Bernard - Lyon1 CERMEP - Imagerie du vivant Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire 59 Bd Pinel 69677 Bron - FRANCE tel : 33 (0)4 72 68 86 13 (bureau) tel : 33 (0)4 72 68 86 00 (standard) fax : 33 (0)4 72 68 86 10 ================================================================== ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr. Achim Bachem (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Kennen Sie schon unseren neuen Film? http://www.fz-juelich.de/film Kennen Sie schon unsere app? http://www.fz-juelich.de/app