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Chusyd DE, Austad SN, Brown AW, Chen X, Dickinson SL, Ejima K, Fluharty D, Golzarri-Arroyo L, Holden R, Jamshidi-Naeini Y, Landsittel D, Lartey S, Mannix E, Vorland CJ, Allison DB. From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research. J Gerontol A Biol Sci Med Sci 2021; 77:2155-2164. [PMID: 34950945 PMCID: PMC9678201 DOI: 10.1093/gerona/glab382] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Indexed: 12/26/2022] Open
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.
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Affiliation(s)
- Daniella E Chusyd
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Steven N Austad
- Department of Biology, University of Alabama at Birmingham, Birmingham, Alabama, USA,Nathan Shock Center, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Andrew W Brown
- Department of Applied Health Science, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Xiwei Chen
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Stephanie L Dickinson
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Keisuke Ejima
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - David Fluharty
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA,Departments of Mathematics and Economics, Ivy Tech Community College, Columbus, Indiana, USA
| | - Lilian Golzarri-Arroyo
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Richard Holden
- Department of Health and Wellness Design, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Yasaman Jamshidi-Naeini
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Doug Landsittel
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Stella Lartey
- Department of Epidemiology and Biostatistics, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Edward Mannix
- Department of Anatomy, Cell Biology, and Physiology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Colby J Vorland
- Department of Applied Health Science, Indiana University Bloomington, Bloomington, Indiana, USA
| | - David B Allison
- Address correspondence to: David B. Allison, PhD, Department of Epidemiology and Biostatistics, Indiana University Bloomington, 1025 E. 7th St., PH 111, Bloomington, IN 47405, USA. E-mail:
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Vorland CJ, Brown AW, Dawson JA, Dickinson SL, Golzarri-Arroyo L, Hannon BA, Heo M, Heymsfield SB, Jayawardene WP, Kahathuduwa CN, Keith SW, Oakes JM, Tekwe CD, Thabane L, Allison DB. Errors in the implementation, analysis, and reporting of randomization within obesity and nutrition research: a guide to their avoidance. Int J Obes (Lond) 2021; 45:2335-2346. [PMID: 34326476 PMCID: PMC8528702 DOI: 10.1038/s41366-021-00909-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 06/26/2021] [Accepted: 07/06/2021] [Indexed: 02/06/2023]
Abstract
Randomization is an important tool used to establish causal inferences in studies designed to further our understanding of questions related to obesity and nutrition. To take advantage of the inferences afforded by randomization, scientific standards must be upheld during the planning, execution, analysis, and reporting of such studies. We discuss ten errors in randomized experiments from real-world examples from the literature and outline best practices for their avoidance. These ten errors include: representing nonrandom allocation as random, failing to adequately conceal allocation, not accounting for changing allocation ratios, replacing subjects in nonrandom ways, failing to account for non-independence, drawing inferences by comparing statistical significance from within-group comparisons instead of between-groups, pooling data and breaking the randomized design, failing to account for missing data, failing to report sufficient information to understand study methods, and failing to frame the causal question as testing the randomized assignment per se. We hope that these examples will aid researchers, reviewers, journal editors, and other readers to endeavor to a high standard of scientific rigor in randomized experiments within obesity and nutrition research.
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Affiliation(s)
- Colby J Vorland
- Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA.
| | - Andrew W Brown
- Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - John A Dawson
- Department of Nutritional Sciences, Texas Tech University, Lubbock, TX, USA
| | - Stephanie L Dickinson
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - Lilian Golzarri-Arroyo
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - Bridget A Hannon
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Moonseong Heo
- Department of Public Health Sciences, Clemson University, Clemson, SC, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA
| | - Wasantha P Jayawardene
- Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - Chanaka N Kahathuduwa
- Department of Psychiatry, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Scott W Keith
- Department of Pharmacology and Experimental Therapeutics, Division of Biostatistics, Thomas Jefferson University, Philadelphia, PA, USA
| | - J Michael Oakes
- Department of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Carmen D Tekwe
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA
| | - Lehana Thabane
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
| | - David B Allison
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA.
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Adams JB, Audhya T, Geis E, Gehn E, Fimbres V, Pollard EL, Mitchell J, Ingram J, Hellmers R, Laake D, Matthews JS, Li K, Naviaux JC, Naviaux RK, Adams RL, Coleman DM, Quig DW. Reply to "Comment on: Comprehensive Nutritional and Dietary Intervention for Autism Spectrum Disorder-A Randomized, Controlled 12-Month Trial, Nutrients 2018, 10, 369". Nutrients 2019; 11:nu11051138. [PMID: 31121871 PMCID: PMC6566397 DOI: 10.3390/nu11051138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 05/16/2019] [Indexed: 11/16/2022] Open
Affiliation(s)
- James B Adams
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | | | - Elizabeth Geis
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | - Eva Gehn
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | - Valeria Fimbres
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | - Elena L Pollard
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | - Jessica Mitchell
- Southwest College of Naturopathic Medicine, Tempe, AZ 85282, USA.
| | - Julie Ingram
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | | | - Dana Laake
- Dana Laake Nutrition, Kensington, MD 20895, USA.
| | | | - Kefeng Li
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego, CA 92093, USA.
| | - Jane C Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego, CA 92093, USA.
| | - Robert K Naviaux
- The Mitochondrial and Metabolic Disease Center, University of California, San Diego, CA 92093, USA.
| | - Rebecca L Adams
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
| | - Devon M Coleman
- School for Engineering of Matter, Transport & Energy, Arizona State University, Tempe, AZ 85287, USA.
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