Evidence map›Paper›PMID 39301794›Full record

ReviewLaboratory animals2024

Bayesian statistical concepts with examples from rodent toxicology studies.

Gary J Larson, Keith R Shockley

Abstract readReview
In one paragraph

Review in Laboratory animals, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Gary J LarsonSocial & Scientific Systems, Inc., a DLH Holdings Corp Company, Durham, USA.ORCID 0000-0001-9998-9573
Keith R ShockleyDivision of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, USA.

Funding

Intramural NIH HHS Z99 ES999999
6 · The paper itself

Abstract

The theory and practice of statistics comprises two main schools of thought: frequentist statistics and Bayesian statistics. Frequentist methods are most commonly used to analyze animal-based laboratory data, while Bayesian statistical methods have been implemented less widely and may be relatively unfamiliar to practitioners in experimental science. This paper provides a high-level overview of Bayesian statistics and how they compare with frequentist methods. Using examples in rodent toxicity research, we argue that Bayesian methods have much to offer laboratory animal researchers. We advocate for increased attention to and adoption of Bayesian methods in laboratory animal research. Bayesian statistical theory, methods, software, and education have advanced significantly in the last 30 years, making these tools more accessible than ever.

Indexed as

Bayes TheoremToxicologyAnimalsRatsRodentiaBayesian statisticshierarchical modelingprior distributionsrodent toxicologystatistical software

Identifiers

PMID39301794
PMCPMC11559269

What OpenQuestion holds

Textmetadata
LicenceTDM
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.