[R-meta] selection models in metafor with step truncation

-----Original Message-----
From: R-sig-meta-analysis <r-sig-meta-analysis-bounces at r-project.org> On Behalf
Of James Pustejovsky via R-sig-meta-analysis
Sent: Saturday, August 3, 2024 04:39
To: R meta <r-sig-meta-analysis at r-project.org>
Cc: James Pustejovsky <jepusto at gmail.com>
Subject: [R-meta] selection models in metafor with step truncation

Hi Wolfgang,

I see in the metafor documentation for selmodel (
https://wviechtb.github.io/metafor/reference/selmodel.html#half-normal-negative-
exponential-logistic-and-power-selection-models)
that the half-normal, negative exponential, logistic, and power curve
selection models can take a value for the step argument, as in the
following code:

library(metafor)
dat <- dat.hahn2001
res <- rma(yi, vi, data=dat, method="REML")
selmodel(res, type="halfnorm", alternative="less")
selmodel(res, type="halfnorm", alternative="less", step = .025)

From the description in the documentation, I wasn't sure how the step
truncation is implemented. Say that the step threshold is called a, the
p-value from study i is p_i, and the selection parameter is delta. Say that
the non-truncated weight function is w(p_i). For a > 0, is the weight
function
min(1, w(p_i) / w(a))
which you might call a "vertical" re-scaling? Or is it
ifelse(p_i < a, 1, w((p_i - a) / (1 - a)))
which you might call a "horizontal" re-scaling?

I think for at least some of the selmodel types listed, the vertical and
horizontal rescalings give different shapes. Could you clarify?

Best,
James