[R-sig-ME] How to fix the value of random intercepts (lmer/MCMCglmm)

[PATRICK, Samantha]

Hi Jarrod

The structure of the data is:

Y = Cumulative number of offspring.
X = Age.  Age is mean centred so the intercept is at 22 years old.  This is where the intercepts are fitted and for each individual I have an exact number of offspring at this age.

I want to examine how the number of offspring increases with age.  I am using random slopes to examine within individual changes with age.  If I don't constrain the intercept at the individual level then the slope does not represent the actual increase with age, and you get results that are largely driven by the age at last sampling.   If I constrain the intercepts, as I understand, the slope will represent the actual increase in fitness with age for each individual.

Happy to post data if this is not clear enough/it would help.

Thanks

Sam


Dr Samantha Patrick
Research Fellow
Biosciences QU116
Francis Close Hall Campus
University of Gloucestershire
Cheltenham, GL50 4AZ, UK

Research Associate: OxNav, University of Oxford

******From 1st August - 14th November 2014 I will be
based in Montréal, which is 5 hours behind GMT  ******

Tel: 07740 472 719
Skype: sammy_patrick
https://sites.google.com/site/samanthacpatrick/

From: Jarrod Hadfield<mailto:j.hadfield at ed.ac.uk>
Sent: ‎Monday‎, ‎25‎ ‎August‎ ‎2014 ‎11‎:‎33
To: Samantha Patrick<mailto:spatrick at glos.ac.uk>
Cc: r-sig-mixed-models at r-project.org<mailto:r-sig-mixed-models at r-project.org>

Hi Sam,

You could do this in MCMCglmm but it sounds like it might (possibly)
be a bad idea. Could you give more details on how Y is actually
obtained?

Cheers,

Jarrod


Quoting "PATRICK, Samantha" <spatrick at glos.ac.uk> on Mon, 25 Aug 2014
15:16:27 +0000:

> Hi All
>
> I am fitting a basic linear regression, where I want to estimate a
> single population intercept and slope.  In addition I am fitting
> random intercepts and slopes such that:
>
> lmer (Y ~Intercept + Continuous Variable + (Continuous Variable
> |Indiviudal Group))
>
> However the exact value of the individual group intercepts is known
> from the data set.  The reasons for this are a little involved but
> essentially Y is a cumulative total and so at the intercept I want
> to fit the actual cumulative total at this point for each
> individual.  It is important as the slope per individual needs to be
> constrained to pass through the actual intercept per individual.
>
> So I want to fit this model, estimating the population intercept and
> slope.  I then want to fix the individual group deviation from the
> population intercept (random intercepts), and from this model
> extract estimates of individual group random slopes.
>
> I have been unable to find any examples of fixing intercepts, unless
> they are fixed as a constant.  Is it possible to code the model in
> such a way? The model can be run in MCMCglmm or lmer  which ever
> package would allow me to constrain the intercepts.
>
> Thanks
>
> Sam​
>
>
> Dr Samantha Patrick
> Research Fellow
> Biosciences QU116
> Francis Close Hall Campus
> University of Gloucestershire
> Cheltenham, GL50 4AZ, UK
>
> Research Associate: OxNav, University of Oxford
>
> ******From 1st August - 14th November 2014 I will be
> based in Montréal, which is 5 hours behind GMT  ******
>
> Tel: 07740 472 719
> Skype: sammy_patrick
> https://sites.google.com/site/samanthacpatrick/
>
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