Evidence map›Paper›PMID 42130610›Full record

ArticleAnnual review of statistics and its application2026

Statistical Methods in Aging Research: Improving Current Practices and Embracing Emerging Approaches.

Deependra K Thapa, Erik S Parker, Mounika Kandukuri, Xi Rita Wang, Thirupathi R Mokalla, Olivia C Robertson, Wasiuddin Najam, Andrew E Teschendorff, Andrew W Brown, John R Speakman and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annual review of statistics and its application, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Deependra K ThapaDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
Erik S ParkerDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
Mounika KandukuriUSDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Xi Rita WangUSDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Thirupathi R MokallaUSDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Olivia C RobertsonUSDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Wasiuddin NajamDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
Andrew E TeschendorffCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.
Andrew W BrownDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
John R SpeakmanSchool of Biological Sciences, University of Aberdeen, Aberdeen, UK.
Yisheng PengDepartment of Organizational Sciences and Communication, George Washington University, Washington, DC, USA.
Bernard S GormanGordon F. Derner School of Psychology, Adelphi University, Garden City, New York, USA.
Heping ZhangDepartment of Statistics and Data Science, Yale University, New Haven, Connecticut, USA.
Luis-Enrique Becerra-GarciaDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
Colby J VorlandDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
David B AllisonDepartment of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.

Funding

Expanding Translational Research in ArkansasUL1TR003107 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI JAMES, LAURA P · 2019 to 2023
$21.6M
Sex hormones and arthritis in a long lived animal modelP30AG050886 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Jianhua Zhang · 2015 to 2026
$11.3M
Nathan Shock Centers Coordinating CenterU24AG056053 · NIA · AMERICAN FEDERATION FOR AGING RESEARCH · PI STEVEN N. AUSTAD, Stephanie Lederman · 2017 to 2026
$6.1M
Strengthening Causal Inference in Behavioral Obesity ResearchR25HL124208 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ALLISON, DAVID B, BROWN, ANDREW W · 2014 to 2023
$1.8M
The Mathematical Sciences in Obesity ResearchR25DK099080 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DAVID B ALLISON, Andrew W Brown · 2013 to 2026
$1.2M
SCISIPBIO: Maximizing rigor and reproducibility when considering Sex as a Biological Variable in researchR01GM152543 · NIGMS · EMORY UNIVERSITY · PI DONNA L MANEY, Colby Vorland · 2023 to 2026
$734k
NCATS NIH HHS UL1 TR003107NHLBI NIH HHS R25 HL124208NIA NIH HHS P30 AG050886NIA NIH HHS U24 AG056053NIDDK NIH HHS R25 DK099080NIGMS NIH HHS R01 GM152543
6 · The paper itself

Abstract

Aging research relies on varied statistical methods, and applying these methods appropriately is important for scientific rigor. However, proper use of these statistical techniques is a challenge. We discuss two categories of statistical methods in aging research: (

Indexed as

aging researchcompression of morbiditydata analysisgerosciencestatistical methodsstatistical rigor

Identifiers

PMID42130610
PMCPMC13166127

What Socratic 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 Socratic graph.