There are functions in the emdbook, metafor, and car packages that do some version of the delta method (although people use "delta method" to refer both to adjusting E[f(y)] using a second-order correction [since the first-order term disappears] and to adjusting V[f(y)] using a first-order correction ...)
emmeans also has such capabilities, search the vignettes for "bias correction" cheers Ben Bolker On Thu, Mar 19, 2026 at 8:57 AM Christofer Bogaso <[email protected]> wrote: > > Hi, > > In many case, we need to transform the dependent variable before > fitting a regression equation, to make it "well-behaved" like close to > normal curve etc. > > like, > > f(y) = alpha + beta1 X1 + beta2 X2 + ... + epsilon > > Now for prediction, R will typically calculate E[f(y)] based on the > fitted coefficients. However, in real scenario, we actually need to > find E[y]. > > Typically, we perform reverse transformation like on fitted E[f(y)] directly. > > However, I believe that in this process, we also need to make some > additional correction for non-linearity in the f() to correctly > calculate E[y]. Onr possible way to do it, may be using Taylors > approximation. > > My question is there any R function that would directly do that based > on the shape of f()? > > Thanks for your time. > > ______________________________________________ > [email protected] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide https://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [email protected] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide https://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
