Evidence map›Paper›PMID 36725775›Full record

ArticlePsychometrika2023

Accurate Confidence and Bayesian Interval Estimation for Non-centrality Parameters and Effect Size Indices.

Kaidi Kang, Megan T Jones, Kristan Armstrong, Suzanne Avery, Maureen McHugo, Stephan Heckers, Simon Vandekar

Abstract read
In one paragraph

Article in Psychometrika, 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. Observational
  5. Canonical babbling trajectories across the first year of life in autism and typical development.Autism : the international journal of research and practice · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. 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

7 authors.

Kaidi KangDepartment of Biostatistics, Vanderbilt University, 2525 West End Ave.,#1136, Nashville, TN, 37203, USA. kaidi.kang@vanderbilt.edu.ORCID 0000-0003-0922-5727
Megan T JonesDepartment of Biostatistics, Vanderbilt University, 2525 West End Ave.,#1136, Nashville, TN, 37203, USA.
Kristan ArmstrongDepartment of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, USA.
Suzanne AveryDepartment of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, USA.
Maureen McHugoDepartment of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, USA.
Stephan HeckersDepartment of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, USA.
Simon VandekarDepartment of Biostatistics, Vanderbilt University, 2525 West End Ave.,#1136, Nashville, TN, 37203, USA. simon.vandekar@vumc.org.

Funding

Imaging Hippocampal Function in PsychosisR01MH070560 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HECKERS, STEPHAN · 2005 to 2025
$7.2M
Semiparametric Inference for Psychiatric NeuroimagingR01MH123563 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI VANDEKAR, SIMON NEIL · 2020 to 2024
$2.1M
NIMH NIH HHS R01 MH070560NIMH NIH HHS R01 MH123563
6 · The paper itself

Abstract

Reporting effect size index estimates with their confidence intervals (CIs) can be an excellent way to simultaneously communicate the strength and precision of the observed evidence. We recently proposed a robust effect size index (RESI) that is advantageous over common indices because it's widely applicable to different types of data. Here, we use statistical theory and simulations to develop and evaluate RESI estimators and confidence/credible intervals that rely on different covariance estimators. Our results show (1) counter to intuition, the randomness of covariates reduces coverage for Chi-squared and F CIs; (2) when the variance of the estimators is estimated, the non-central Chi-squared and F CIs using the parametric and robust RESI estimators fail to cover the true effect size at the nominal level. Using the robust estimator along with the proposed nonparametric bootstrap or Bayesian (credible) intervals provides valid inference for the RESI, even when model assumptions may be violated. This work forms a unified effect size reporting procedure, such that effect sizes with confidence/credible intervals can be easily reported in an analysis of variance (ANOVA) table format.

Indexed as

Bayes TheoremAnalysis of VariancePsychometricsanalysis of effect sizebayesian bootstrapbootstrapconfidence intervalcredible intervaleffect sizenon-central Chi-squared distributionnon-central F distributionnon-centrality parameterrobust effect size index

Identifiers

PMID36725775
PMCPMC9977896

What OpenQuestion holds

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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.