[R-sig-ME] Fixed effects in nlmer

[Ben Bolker]

    Nice idea, but I don't see how that would work.  The terms in a 
nonlinear mixed model aren't automatically expanded using linear model 
formulas ...

On 2024-06-17 9:17 a.m., marKo via R-sig-mixed-models wrote:
> Hi.
> 
> How about adding it via an interaction effect?
> Something like: y ~ SSlogis(x, Asym, Asym:lines_cathegorical, xmid, scal)
> The rest should be more or less the same.
> 
> Hope that it make sense.
> 
> 
> Cheers,
> 
> Marko
> 
> 
>   On 17. 06. 2024. 15:05, Jarrod Hadfield wrote:
>> Hi,
>>
>> I would like to use nlmer to fit logistic growth curves to data where 
>> a number of replicate growth series are available for several clonal 
>> lines. Fitting the random effect structure is straightforward:
>>
>> fm1 <- lme4:::nlmer(y ~ SSlogis(x, Asym, xmid, scal) ~  
>> (Asym+xmid+scal | line) + (Asym+xmid+scal | rep), ….)
>>
>> allowing all 3 growth parameters to vary across lines and across 
>> replicates within lines.  However, I’ve had no success adding fixed 
>> effects to the model formula, and the examples on the help page do not 
>> have fixed effect predictors. For example, if lines could be divided 
>> into two groups (A and B) how would I allow Asym to differ between 
>> these two groups?
>>
>> Thanks for any help,
>>
>> Jarrod
>>
>>
>>
>>
>>
>>
>>
>>
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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