Thanks Ben.
Could you please help pointing out names of specific functions on Bias
correction? I searched with like ls('package:emdbook') etc. however
failed to identify relevant functions.
On Thu, Mar 19, 2026 at 6:55 PM Ben Bolker <[email protected]> wrote:
>
> 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.
> >
> > ______________________________________________
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> > PLEASE do read the posting guide
> > https://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
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and provide commented, minimal, self-contained, reproducible code.
