TY - JOUR
T1 - Trial characteristics and appropriateness of statistical methods applied for design and analysis of randomized school-based studies addressing weight-related issues
T2 - A literature review
AU - Heo, Moonseong
AU - Nair, Singh R.
AU - Wylie-Rosett, Judith
AU - Faith, Myles S.
AU - Pietrobelli, Angelo
AU - Glassman, Nancy R.
AU - Martin, Sarah N.
AU - Dickinson, Stephanie
AU - Allison, David B.
N1 - Funding Information:
'is study was in part supported by R01DK097096, P30DK111022, UL1 TR001073, R25DK099080, and R25HL124208.
Publisher Copyright:
© 2018 Moonseong Heo et al.
PY - 2018
Y1 - 2018
N2 - Objective. To evaluate whether clustering effects, often quantified by the intracluster correlation coefficient (ICC), were appropriately accounted for in design and analysis of school-based trials. Methods. We searched PubMed and extracted variables concerning study characteristics, power analysis, ICC use for power analysis, applied statistical models, and the report of the ICC estimated from the observed data. Results. N=263 papers were identified, and N=121 papers were included for evaluation. Overall, only a minority (21.5%) of studies incorporated ICC values for power analysis, fewer studies (8.3%) reported the estimated ICC, and 68.6% of studies applied appropriate multilevel models. A greater proportion of studies applied the appropriate models during the past five years (2013-2017) compared to the prior years (74.1% versus 63.5%, p=0.176). Significantly associated with application of appropriate models were a larger number of schools (p=0.030), a larger sample size (p=0.002), longer follow-up (p=0.014), and randomization at a cluster level (p<0.001) and so were studies that incorporated the ICC into power analysis (p=0.016) and reported the estimated ICC (p=0.030). Conclusion. Although application of appropriate models has increased over the years, consideration of clustering effects in power analysis has been inadequate, as has report of estimated ICC. To increase rigor, future school-based trials should address these issues at both the design and analysis stages.
AB - Objective. To evaluate whether clustering effects, often quantified by the intracluster correlation coefficient (ICC), were appropriately accounted for in design and analysis of school-based trials. Methods. We searched PubMed and extracted variables concerning study characteristics, power analysis, ICC use for power analysis, applied statistical models, and the report of the ICC estimated from the observed data. Results. N=263 papers were identified, and N=121 papers were included for evaluation. Overall, only a minority (21.5%) of studies incorporated ICC values for power analysis, fewer studies (8.3%) reported the estimated ICC, and 68.6% of studies applied appropriate multilevel models. A greater proportion of studies applied the appropriate models during the past five years (2013-2017) compared to the prior years (74.1% versus 63.5%, p=0.176). Significantly associated with application of appropriate models were a larger number of schools (p=0.030), a larger sample size (p=0.002), longer follow-up (p=0.014), and randomization at a cluster level (p<0.001) and so were studies that incorporated the ICC into power analysis (p=0.016) and reported the estimated ICC (p=0.030). Conclusion. Although application of appropriate models has increased over the years, consideration of clustering effects in power analysis has been inadequate, as has report of estimated ICC. To increase rigor, future school-based trials should address these issues at both the design and analysis stages.
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U2 - 10.1155/2018/8767315
DO - 10.1155/2018/8767315
M3 - Review article
C2 - 30046468
AN - SCOPUS:85049825268
SN - 2090-0708
VL - 2018
JO - Journal of obesity
JF - Journal of obesity
M1 - 8767315
ER -