Evidence map›Paper›PMID 38550789›Full record

ArticleJournal of the American Statistical Association2023

Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in "Large

Akihiko Nishimura, Marc A Suchard

Abstract read
In one paragraph

Article in Journal of the American Statistical Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Bayesian Factor Analysis for Inference on Interactions.Journal of the American Statistical Association · 2021
    Article
  10. Article
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

2 authors.

Akihiko NishimuraDepartment of Biostatistics, Johns Hopkins University, Baltimore, MD.ORCID 0000-0002-6932-2513
Marc A SuchardDepartment of Biomathematics, Biostatistics, and Human Genetics, University of California-Los Angeles, Los Angeles, CA.ORCID 0000-0001-9818-479X

Funding

Technology CoreU19AI135995 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI Laura D. Hughes · 2018 to 2026
$32.0M
Statistical Innovation to Integrate Sequences and Phenotypes for Scalable Phylodynamic InferenceR01AI153044 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Marc A. Suchard · 2021 to 2026
$2.4M
NIAID NIH HHS R01 AI153044NIAID NIH HHS U19 AI135995
6 · The paper itself

Abstract

In a modern observational study based on healthcare databases, the number of observations and of predictors typically range in the order of 10

Indexed as

Big dataConjugate gradientMarkov chain Monte CarloNumerical linear algebraSparse matrixVariable selection

Identifiers

PMID38550789
PMCPMC10977663

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.