Hi Jonathan,

I'm pretty sure that the following are identical syntax for correlated
random intercepts and slopes written in 'lmer':

(B|Male) and (1+B|Male)


Your uncorrelated random slopes syntax '(B|Male)' is actually correlated
random intercepts and slopes.  This probably doesn't explain the issue that
I have experiencing, but I appreciate the attempt.

Jacob


On Tue, Apr 15, 2014 at 6:07 PM, Jonathan French <jonathanf@metrumrg.com>wrote:

> Hi Jacob,
>
> I think that you probably want to add a random intercept to your model in
> addition to the random slope (B).  That is, I suspect you want a model like
> this:
>
> model<-lmer(A~B*Year+(1 + B|Male),
>
> or this
>
> model<-lmer(A~B*Year+(1|Male) + (B|Male),
>
> The difference being whether the model estimates a correlation between the
> random intercept and slope (the first model) or not (the second).
>
> Your current model assumes that all males have the same intercept.  So, I
> would guess that the individuals where you see a discrepancy between the
> plot and the BLUP are males who are, on average, well above or below the
> mean at B=0.  For those males, the population average intercept isn't a
> good estimate for their intercept; the model is trying to adjust to the
> extent that it can using only the slope.
>
> I hope that's clear (and somewhat helpful).
>
> best regards,
> Jonathan
>
> *Jonathan French*
> *Metrum Research Group*
> *2 Tunxis Road, Suite 112*
> *Tariffville, CT 06081*
>
>
>
> On Tue, Apr 15, 2014 at 2:00 PM, AvianResearchDivision <
> segerfan83@gmail.com> wrote:
>
>> Hi all,
>>
>> Thank you for answering my previous questions recently.  I have another
>> one
>> for you.  I ran the following model:
>>
>> model<-lmer(A~B*Year+(B|Male),
>>
>> where B is a within-individual mean-centered continuous environmental
>> variable, year is a factor with 2 levels, and Male is a factor with 59
>> levels.
>>
>> Upon creation of a panel plot  with 'B' on the x axis and 'A' on the
>> y-axis
>> and each of the 59 males in a different panel, I noticed that the plot
>> patterns don't correspond to the BLUPs from the prinout coef(model).  For
>> instance, a male that clearly increases 'A' as 'B' increases according to
>> the panel plot, decreases 'A' as 'B' increases according to the BLUPs from
>> coef(model).  This is the case with several of the males.  Am I doing
>> something wrong?  I feel I shouldn't be seeing this pattern.  Any insight
>> would be much appreciated.
>>
>> Thank you,
>> Jacob
>>
>>         [[alternative HTML version deleted]]
>>
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>>
>
>
>
> --
> *Jonathan French*
> *Metrum Research Group*
> *2 Tunxis Road, Suite 112*
> *Tariffville, CT 06081*
> *tel: 860-222-5071 <860-222-5071>*
>
>

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