Recommended sample sizes for nonlinear regression I have tried looking here and elsewhere for information about sample sizes for nonlinear regression, but I'm finding it difficult to get concrete answers on this topic. Specifically, what is the established number of subjects or observations that are generally required? I will be potentially modeling a crossed random effects GAMM and I would imagine this would require a fairly large sample given the complexity of the model. For crossed random effects in GLMM, Brysbaert & Stevens give some recommendations, one being 1600 observations per condition.
Some sources that give too many numbers and vague answers to know for sure:

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*https://www.researchgate.net/post/What_is_the_minumum_number_of_data_required_for_nonlinear_chaotic_analysis

*https://pubmed.ncbi.nlm.nih.gov/15287084/

You probably won't find a single answer because non-linear regression is a catch-all phrase that can mean arbitrarily complicated models. In such a case, it's hard to give any recommendations. Also, keep in mind that most such recommendations are just rules of thumb that do not give any guarantees of correctness. There is even no single (or simple) answer for linear regression or logistic regression not to say about more complicated models.
