From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research

Authors

Daniella E Chusyd
Steven N Austad
Andrew W Brown
Xiwei Chen
Stephanie L Dickinson
Keisuke Ejima
David Fluharty
Lilian Golzarri-Arroyo
Richard Holden
Yasaman Jamshidi-Naeini
Doug Landsittel
Stella Lartey
Edward Mannix
Colby J Vorland
David B Allison

Language

English

Publication Date

11-21-2022

Journal

The Journals of Gerontology: Series A

DOI

10.1093/gerona/glab382

PMID

34950945

PMCID

PMC9678201

PubMedCentral® Posted Date

12-24-2021

PubMedCentral® Full Text Version

Post-print

Abstract

This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: (a) errors in randomization, (b) errors related to testing within-group instead of between-group differences, (c) failing to account for clustering, (d) failing to consider interference effects, (e) standardizing metrics of effect size, (f) maximum life-span testing, (g) testing for effects beyond the mean, (h) tests for power and sample size, (i) compression of morbidity versus survival curve squaring, and (j) other hot topics, including modeling high-dimensional data and complex relationships and assessing model assumptions and biases. We hope that bringing increased awareness of these topics to the scientific community will emphasize the importance of employing sound statistical practices in all aspects of aging and senescence research.

Keywords

Humans, Data Interpretation, Statistical, Research Design, Sample Size, Bias, Aging, Geroscience, Methodologies, Reproducibility

Published Open-Access

yes

Recommended Citation

Chusyd, Daniella E; Austad, Steven N; Brown, Andrew W; et al., "From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research" (2022). Children’s Nutrition Research Center Staff Publications. 200.
https://digitalcommons.library.tmc.edu/staff_pub/200