[R-sig-ME] Time-varying random effects

[Ben Bolker]

  And I'll chime in: how bad is your failure to converge?
  As regular readers of the list know, there are a lot of false
positives. What kind of convergence failures?  Have you checked the
?convergence page ?

On 16-11-24 09:43 AM, Thierry Onkelinx wrote:
> Hi Mark,
> 
> I have some questions on the design.
> - Can you identify the individual pigs in the data?
> - How is the grouping of the pigs? Is it constant (e.g. all pigs from the
> same litter stay together)? Or does the grouping changes over time?
> - Do expect any effect of the pens itself? Or are the pens rather a just
> group of pigs.
> 
> Best regards,
> 
> Thierry
> 
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> 
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
> 
> 2016-11-23 15:58 GMT+01:00 Marc Jacobs <marc.jacobs012 at gmail.com>:
> 
>> Hi,
>>
>>
>>
>> By request of Prof. Bolker, i am posting my question here.
>>
>>
>> I am currently in the process of analyzing a growth model in pigs. Due to
>> the confidentiality of the data, I cannot add any data which is of course
>> the preferred course, but I hope to gain some insight here. I apologize in
>> advance if the description is unclear.
>>
>>
>>
>> The data shows growth in 300+ pigs over 168 days, measured on 11
>> time-points. These 168 days can be divided in three separate phases:
>> farrowing/mom (2 timepoints), nursery (4 timepoints), and growth-finish (5
>> timepoints).
>>
>>
>>
>> During each of these phases, the animals are placed in different rooms and
>> pens (nested in the rooms), which by definition are random factors. Also,
>> there is a genetic dependency of pigs (litter) nested in moms, which would
>> be a crossed effect, since the effect takes place across the entire
>> dataset, separate from the room/pen (pigs are separated from the litter
>> after the farrowing/mom phase).
>>
>>
>>
>> As such, from my point of view, the room/pen are now time-varying random
>> effects. Since I wish to model the entire growth curve, I was wondering if
>> anybody knows how to incorporate time-varying random effects?
>>
>>
>>
>> My gut feeling tells me this is quite easy, but my models do not converge.
>>
>>
>>
>> If you need more information, please let me know.
>>
>>
>>
>> Marc
>>
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>>
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