Using Importance Sampling to Estimate

Samuel Anyaso-Samuel, Thong Luong, Fei Qin, Jiyeon Choi, Kai Yu, Paul S Albert, Jianxin Shi

Abstract readPreprint

In one paragraph

Article in ArXiv, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Samuel Anyaso-SamuelDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Thong LuongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Fei QinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Jiyeon ChoiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Kai YuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Paul S AlbertDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Jianxin ShiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, U.S.A.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pooling genome-wide association studies of multiple related traits can substantially increase power for detecting genetic variants with pleiotropic effects. ASSET, which exhaustively searches all subsets of studies for association signals, has been widely used to detect modest effects and improve interpretability. Under a normality assumption, ASSET computes p-values via an analytic approximation that accounts for multiple testing. However, this approximation has been evaluated only in limited scenarios and for p-values no smaller than 10

Identifiers

PMID42389241

PMCPMC13317650

What Socratic holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.