Evidence map›Paper›PMID 38323449›Full record

ArticleThe Journal of experimental biology2024

Looking beyond the mean: quantile regression for comparative physiologists.

Coen Hird, Kaitlin E Barham, Craig E Franklin

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of experimental biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.2field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Coen HirdSchool of the Environment, The University of Queensland, Brisbane (Magandjin), QLD 4072, Australia.ORCID 0000-0001-9812-4818
Kaitlin E BarhamSchool of the Environment, The University of Queensland, Brisbane (Magandjin), QLD 4072, Australia.ORCID 0000-0002-5631-6261
Craig E FranklinSchool of the Environment, The University of Queensland, Brisbane (Magandjin), QLD 4072, Australia.ORCID 0000-0003-1315-3797
The University of Queensland · AU

Funding

Australian Research Council DP190102152University of Queensland
6 · The paper itself

Abstract

Statistical analyses that physiologists use to test hypotheses predominantly centre on means, but the tail ends of the response distribution can behave quite differently and underpin important scientific phenomena. We demonstrate that quantile regression (QR) offers a way to bypass some limitations of least squares regression (LSR) by building a picture of independent variable effects across the whole distribution of a dependent variable. We used LSR and QR with simulated and real datasets. With simulated data, LSR showed no change in the mean response but missed significant effects in the tails of the distribution found using QR. With real data, LSR showed a significant change in the mean response but missed a lack of response in the upper quantiles which was biologically revealing. Together, this highlights that QR can help to ask and answer more questions about variation in nature.

Indexed as

Research DesignRegression AnalysisBiostatisticsMedian regressionOrdinary least squaresPercentilesStatistical toolbox

Identifiers

PMID38323449
PMCPMC10949063
OpenAlexW4391613215

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.