In human words, we the random effects can be described as follows:
We believe that the variability comes from each subject behaving uniquely at
each period and from each eye of each subject at each period behaving
uniquely.
As far as the crash, I've compiled a structurally-similar dataset (withou
Hi,
I have found Pinheiro and Bates an absolute godsend for mixed modelling,
http://www.amazon.com/Mixed-Effects-Models-S-S-Plus/dp/0387989579
alternatively, there is a REALLY good chapter in the 3rd edition of DAAG:
http://www.amazon.com/Data-Analysis-Graphics-Using-Example-Based/dp/05217629
JaFF gmail.com> writes:
>
>
> Hi bbolker,
>
> bbolker wrote:
> >
> > Doesn't "treatment" appear in fixed effects somewhere? Perhaps you mean
> > (Treatment+Period+Dose):Eye?
>
> Apologies for the confusion. What you referred to as "Treatment", I called
> "Dose" in my post. So in your terms,
Hi bbolker,
bbolker wrote:
>
> Doesn't "treatment" appear in fixed effects somewhere? Perhaps you mean
> (Treatment+Period+Dose):Eye?
Apologies for the confusion. What you referred to as "Treatment", I called
"Dose" in my post. So in your terms, to avoid confusion, the fixed effects
are (Subj
JaFF gmail.com> writes:
>
>
> Hi folks,
>
> I have a dataset from a trial measuring the subjects' pupils. There are many
> measurements, all of which must be analysed in a similar fashion; so if I
> get the analysis right for one of them, I've got them all. For simplicity,
> let us call any me
Hi folks,
I have a dataset from a trial measuring the subjects' pupils. There are many
measurements, all of which must be analysed in a similar fashion; so if I
get the analysis right for one of them, I've got them all. For simplicity,
let us call any measurement we may be interested as "response
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