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2026 · Review · Annual review of statistics and its application

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; Yisheng Peng; Bernard S Gorman; Heping Zhang; Luis-Enrique Becerra-Garcia; Colby J Vorland; David B Allison

Reviews established and emerging statistical methods for aging research, including lifespan analysis, aging clocks, treatment heterogeneity, and dependent observations.

Open-science resources

Resource verification & source notes
  • Free full text (PMC): The complete article body was retrieved from the public NCBI PMC JATS endpoint. This confirms free access; reuse permissions depend on the individual article license.

Publication details

Research themes

Statistical rigorNutrition & aging

aging · preclinical-research

Author affiliations & identifiers
  • Deependra K Thapa: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
  • Erik S Parker: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
  • Mounika Kandukuri: USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
  • Xi Rita Wang: USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
  • Thirupathi R Mokalla: USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
  • Olivia C Robertson: USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
  • Wasiuddin Najam: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
  • Andrew E Teschendorff: CAS 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 Brown: Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.; Arkansas Children's Research Institute, Little Rock, Arkansas, USA.
  • John R Speakman: School of Biological Sciences, University of Aberdeen, Aberdeen, UK.
  • Yisheng Peng: Department of Organizational Sciences and Communication, George Washington University, Washington, DC, USA.
  • Bernard S Gorman: Gordon F. Derner School of Psychology, Adelphi University, Garden City, New York, USA.
  • Heping Zhang: Department of Statistics and Data Science, Yale University, New Haven, Connecticut, USA.
  • Luis-Enrique Becerra-Garcia: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
  • Colby J Vorland: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.
  • David B Allison: Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Indiana, USA.; USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA.
Source notes
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Metadata sources: PubMed, OpenAlex, CV, Google Scholar. Classification is an editorial interpretation of the title, abstract, and supplied CV.