[R-sig-ME] The effects of adding by-subject or by-item random intercepts
Daniel Ezra Johnson
danielezrajohnson at gmail.com
Tue Dec 8 19:24:33 CET 2009
The choice is in theory between treating Item as a random effect or a
fixed effect. Not in my view omitting it totally.
In practice you have to use a random effect or a singularity (non-
estimable model) results.
Dan
Tremblay <trea26 at gmail.com> wrote:
> Thank you for your replies.
> :-)
>
> Let's see if I understood well. Say I test for a frequency effect
> (high vs low) ReactionTime ~ Frequency without the by-items random
> intercepts and find a difference.
>
> Now in a model where I do include by-items random intercepts
> ReactionTime ~ Frequency + (1|Item) the frequency effect disappears.
>
> Then the frequency effect found in the model without by-item random
> intercepts was spurious, i.e., was due only to within group
> variability and not to a true population effect. Is that right?
>
> Now say I have created artificial items, which I used in my
> experiment. I thus have all the whole population of items. Should I
> still include Items as a random effect? If it is the case, then,
> including or not a random effect is not only a matter of wanting to
> generalize over subjects or items, but rather a matter of getting rid
> of, so to speak, within-group variability, which, if uncontrolled for,
> may lead to spurious effects. Is that right?
>
> Thank you again for your help.
> Sincerely,
>
> Antoine
>
> On Tue, Dec 8, 2009 at 7:38 AM, Daniel Ezra Johnson
> <danielezrajohnson at gmail.com> wrote:
>> Shrinkage is not the main issue, as I see it here. When the
>> predictor of
>> interest is Sex you should include by-subject random effect(s),
>> when it's
>> Frequency you should include by-item. Probably you should include
>> both in
>> both cases. You can't do accurate hypothesis testing on Sex and
>> Frequency if
>> you ignore the variation among Subjects and Items.
>>
>> On Dec 8, 2009, at 2:15 AM, Antoine Tremblay <trea26 at gmail.com>
>> wrote:
>>
>>> Dear all,
>>>
>>> This question is about the effects of adding by-subject or by-item
>>> random intercepts to a model.
>>>
>>> If we are contrasting a single condition between two subject groups,
>>> say ReactionTime ~ Sex,
>>> is it warranted (or necessary or ill-advised) to include by-subjects
>>> random intercepts,
>>> since this could (if I'm understanding it correctly) adjust the mean
>>> reaction time for each subject (and thus for
>>> each condition) towards the grand mean, thus reducing or
>>> eliminating the difference in the condition between subjects? And
>>> similarly if we are contrasting a
>>> single condition between two sets of items, say ReactionTime ~
>>> Frequency?
>>>
>>> I believe that the addition of the random effect may reduce the
>>> effect
>>> of the fixed effect, but should
>>> not remove it entirely. Is this right?
>>>
>>> The question would then become: Why would the addition of say by-
>>> item
>>> random intercepts to a model
>>> take away an effect that was present in a model without by-item
>>> random
>>> intercepts?
>>>
>>> Thank you again, your help is well appreciated.
>>>
>>> --
>>> Antoine Tremblay
>>> Department of Neuroscience
>>> Georgetown University
>>> Washington DC
>>>
>>> _______________________________________________
>>> R-sig-mixed-models at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
>
> --
> Antoine Tremblay
> Department of Neuroscience
> Georgetown University
> Washington DC
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