Personalised Decision-Making without Counterfactuals

A. Philip Dawid; Stephen Senn

Personalised Decision-Making without Counterfactuals

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2301.11976 v2 pith:FZZ3HTNT submitted 2023-01-27 stat.ME math.STstat.TH

A. Philip Dawid , Stephen Senn This is my paper · ORCID

classification stat.MEmath.STstat.TH

keywords approachpersonalisedarguearticlecontrastcounterfactualsdangerouslydecision

verification ladder T0 review T1 audit T2 compute T3 formal

0 comments

read the original abstract

This article is a response to recent proposals by Pearl and others for a new approach to personalised treatment decisions, in contrast to the traditional one based on statistical decision theory. We argue that this approach is dangerously misguided and should not be used in practice.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Individual Treatment Effect: Prediction Intervals and Sharp Bounds
stat.ME 2025-06 conditional novelty 6.0 of 10

Valid prediction intervals for individual treatment effects from large RCTs are trivial unless response rates are extreme, and sharp pmf bounds are given by sums of Fréchet cell bounds.

Pith tools