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
<bogaso.christofer at gmail.com> 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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