Fixed effects in nlmer
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 The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th? ann an Oilthigh Dh?n ?ideann, cl?raichte an Alba, ?ireamh cl?raidh SC005336.
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