Dear Sebastien, On 2020-07-28 14:13 +0000, Sebastien Bihorel wrote: | Hi | | I need to fit a logistic regression | model using a saturable | Michaelis-Menten function of my | predictor x. The likelihood could be | expressed as: | | L = intercept + emax * x / (EC50+x) | | Which I guess could be expressed as | the following R model | | ~ emax*x/(ec50+x) | | As far as I know (please, correct me | if I am wrong), fitting such a model | is to not doable with glm, since the | function is not linear. | | A Stackoverflow post recommends the | bnlr function from the gnlm | (https://stackoverflow.com/questions/45362548/nonlinear-logistic-regression-package-in-r)... | I would be grateful for any opinion on | this package or for any alternative | recommendation of package/function.
I found base stats has the function stats::SSmicmen, also this page[1] mentions stats::nls ... I found cardioModel::cardioModel ... You need Google V8[3] which takes forever to build. Also the emaxmodel vignette[4] might be useful, as it mentions both EC50 and Emax. Best, Rasmus [1] https://dataconomy.com/2017/08/nonlinear-least-square-nonlinear-regression-r/ [2] https://www.rdocumentation.org/packages/cardioModel/versions/1.4/topics/cardioModel [3] https://v8.dev/ [4] https://cran.r-project.org/web/packages/rstanemax/vignettes/emaxmodel.html ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
