TY - JOUR
T1 - Errors in the implementation, analysis, and reporting of randomization within obesity and nutrition research
T2 - a guide to their avoidance
AU - Vorland, Colby J.
AU - Brown, Andrew W.
AU - Dawson, John A.
AU - Dickinson, Stephanie L.
AU - Golzarri-Arroyo, Lilian
AU - Hannon, Bridget A.
AU - Heo, Moonseong
AU - Heymsfield, Steven B.
AU - Jayawardene, Wasantha P.
AU - Kahathuduwa, Chanaka N.
AU - Keith, Scott W.
AU - Oakes, J. Michael
AU - Tekwe, Carmen D.
AU - Thabane, Lehana
AU - Allison, David B.
N1 - Funding Information:
CJV is supported in part by the Gordon and Betty Moore Foundation. DBA and AWB are supported in part by NIH grants R25HL124208 and R25DK099080. SBH is supported in part by National Institutes of Health NORC Center Grants P30DK072476, Pennington/Louisiana and P30DK040561, Harvard. CDT research is supported by National Cancer Institute Supplemental Award Number U01-CA057030-29S2. Other authors received no specific funding for this work. The opinions expressed are those of the authors and do not necessarily represent those of the NIH or any other organization.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/11
Y1 - 2021/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85111662122&partnerID=8YFLogxK
U2 - 10.1038/s41366-021-00909-z
DO - 10.1038/s41366-021-00909-z
M3 - Review article
C2 - 34326476
AN - SCOPUS:85111662122
VL - 45
SP - 2335
EP - 2346
JO - International Journal of Obesity
JF - International Journal of Obesity
SN - 0307-0565
IS - 11
ER -