[R-sig-ME] r crossed nested random effects lme4

[Phillip Alday]

Yes, use that model. Since Items are nested within conditions, it
doesn't make sense to have an by-item slope for condition.

Phillip

On 06/29/2018 10:25 AM, audusseau jean wrote:
> Phillip,
> 
> Many thanks for your answer. I apologize for such an unclear description
> of my experiment. I wanted to make it simpler but it seems I produced
> the opposite.
> 
> In fact, my experiment consists of :
> 
> - _71_ subjects
> 
> - going through 3 conditions (so "condition" and "subject" are crossed)
> 
> - each condition comprises _30_ items (so items are nested in conditions)
> 
> Concerning the dependant variable, I use 1/RT.
> 
> As I understand your comments, I should acknowledge that the condition
> effect may vary for different subjects. So I thought a better model may be:
> 
> 1/RT~1+condition+(condition|subject) +(1| item)
> 
> Given that I have 30 items in each condition, would you advice to modify
> the last term of this syntax ?
> 
> Thank you for your time.
> 
> 
> 
> Le jeudi 28 juin 2018 à 21:59:56 UTC+2, Alday, Phillip
> <Phillip.Alday using mpi.nl> a écrit :
> 
> 
> lme4 doesn't force a hard nested-crossed distinction and can handle
> implicit nesting/crossing easily (assuming unique identifiers, which you
> have), so you don't have to worry about that.
> 
> The only "problem" I see with your model is that it is an
> "intercept-only" model. Given that there are only three items per
> condition, this makes sense for the by-item random effect. But you
> should consider whether the by-subject random effect should have a slope
> for condition. This is all assuming that you only sent us a screenshot
> of the top of the dataset and that you have more than three subjects ...
> 
> There are some more general issues about whether you should transform
> reaction time, but a quick search will yield lots of papers discussing
> the pros and cons of that.
> 
> Finally, please be kind to the list and be consistent in your names --
> you swap back and forth between Group and Cond in your description.
> 
> Phillip
> 
> 
> On 28/06/18 09:13, audusseau jean via R-sig-mixed-models wrote:
>> Dear all,I try to find the appropriate model for the following data set with lme4:
>> Each individual subject goes through 3 conditions ("Group", within-subject factor). These 3 conditions include 9 items (3 items in each condition, but the items differ in each condition). Score (4th column not represented above) is a continuous dependant variable (reaction time).I am interested in the fixed effect of the "Cond" variable and also would like to take into account the dependencies between my factors, but I have difficulties to know if my factors should be considered as nested or crossed.Does the following model seems correct to you ?Score~1+Cond+(1|Subject)+(1|item).Any help would be much appreciated.
>>
>>
>>
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