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This topic contains 2 replies, has 2 voices, and was last updated by Matej Hruska 2 weeks, 5 days ago.

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May 31, 2017 at 05:39 UTC #72
Dear fellow modelers,
I am trying to figure out whether it is possible to make a mixed anova model asymmetrical (meaning having an “independent” control group) – my design is 2×2 factors + (possibly) 1 control group (so 5 experimental conditions), repeated measures pretest / posttest (in each condition).
Or is there some other more sensible way to measure group differences and interactions?Thanks,
Matej 
May 31, 2017 at 08:34 UTC #73
In principle mixed models have the same constraint as all statistical models that you cannot estimate parameters for cells or conditions where you have no data at all (i.e., structurally missing). For example, when your control condition does not interact with one other factor (e.g., for your factor
A
, the control condition only exists for levela1
and not for levela2
) then you cannot have an interaction ofA
withcontrol
.As far as I understand your design you have 5 betweensubjects or independentsamples groups. For each unit of observation in this group you furthermore have pretest and posttest observations. This would allow to model the data as a 5 x 2 design with factors
group
andtest_time
:~ group*test_time + (test_timeid)
(note that the random effects structure assumes that you have replicates for each unit of observation andtest_time
condition, which you probably should have)The problem with this approach is obviously that it flattens out the 2 x 2 design underlying 4 of your 5 groups. I do not see a way how to incorporate this structure with the control in one model. I think there are two ways to address the 2 x 2 structure subsequently, once you have run the initial model and have determined how the control group relates to the other 4 groups. You could either test the 2 x 2 design from the initial model using
lsmeans
(using a combination oflsmeans
,contrast
, andtest
) or run a second model on the reduced data that has a 2 x 2 x 2 design (i.e., your 4 groups times the repeatedmeasures factor). The second approach seems somewhat more straight forward to implement. This reply was modified 4 weeks ago by henrik. Reason: clarified ranom effects structure

June 9, 2017 at 11:31 UTC #84
Dear Henrik,
thanks for your answer! sorry for a delayed reaction, I didnt receive an email notification…
It looks like we will simplify the design and maybe do two separate experiments, so the structure will be more straightforward.
Best,
Matej

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