Connection

DAVID ALLISON to Research Design

This is a "connection" page, showing publications DAVID ALLISON has written about Research Design.
Connection Strength

9.171
  1. Ambiguity in Statistical Analysis Methods and Nonconformity With Prespecified Commitment to Data Sharing in a Cluster Randomized Controlled Trial. J Med Internet Res. 2024 Apr 03; 26:e54090.
    View in: PubMed
    Score: 0.684
  2. 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. 2022 11 21; 77(11):2155-2164.
    View in: PubMed
    Score: 0.622
  3. A practical decision tree to support editorial adjudication of submitted parallel cluster randomized controlled trials. Obesity (Silver Spring). 2022 03; 30(3):565-570.
    View in: PubMed
    Score: 0.591
  4. Evaluation of the type I error rate when using parametric bootstrap analysis of a cluster randomized controlled trial with binary outcomes and a small number of clusters. Comput Methods Programs Biomed. 2022 Mar; 215:106654.
    View in: PubMed
    Score: 0.587
  5. Errors in the implementation, analysis, and reporting of randomization within obesity and nutrition research: a guide to their avoidance. Int J Obes (Lond). 2021 11; 45(11):2335-2346.
    View in: PubMed
    Score: 0.568
  6. Data anomalies and apparent reporting errors in 'Randomized controlled trial testing weight loss and abdominal obesity outcomes of moxibustion'. Biomed Eng Online. 2020 Feb 18; 19(1):11.
    View in: PubMed
    Score: 0.514
  7. Best (but oft-forgotten) practices: identifying and accounting for regression to the mean in nutrition and obesity research. Am J Clin Nutr. 2020 02 01; 111(2):256-265.
    View in: PubMed
    Score: 0.512
  8. Trial Characteristics and Appropriateness of Statistical Methods Applied for Design and Analysis of Randomized School-Based Studies Addressing Weight-Related Issues: A Literature Review. J Obes. 2018; 2018:8767315.
    View in: PubMed
    Score: 0.458
  9. Issues with data and analyses: Errors, underlying themes, and potential solutions. Proc Natl Acad Sci U S A. 2018 03 13; 115(11):2563-2570.
    View in: PubMed
    Score: 0.449
  10. Scientific rigor and credibility in the nutrition research landscape. Am J Clin Nutr. 2018 03 01; 107(3):484-494.
    View in: PubMed
    Score: 0.448
  11. Stated conclusion about industry funding is opposite to what the paper's data show: letter regarding 'Selective outcome reporting in obesity clinical trials: a cross-sectional review'. Clin Obes. 2017 12; 7(6):402.
    View in: PubMed
    Score: 0.433
  12. Randomization to randomization probability: Estimating treatment effects under actual conditions of use. Psychol Methods. 2018 Jun; 23(2):337-350.
    View in: PubMed
    Score: 0.422
  13. Common scientific and statistical errors in obesity research. Obesity (Silver Spring). 2016 Apr; 24(4):781-90.
    View in: PubMed
    Score: 0.392
  14. Reproducibility: A tragedy of errors. Nature. 2016 Feb 04; 530(7588):27-9.
    View in: PubMed
    Score: 0.388
  15. Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials. Am J Clin Nutr. 2015 Aug; 102(2):241-8.
    View in: PubMed
    Score: 0.370
  16. Getting carried away: a note showing baseline observation carried forward (BOCF) results can be calculated from published complete-cases results. Int J Obes (Lond). 2012 Jun; 36(6):886-9.
    View in: PubMed
    Score: 0.277
  17. Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research. Obes Rev. 2023 Dec; 24(12):e13635.
    View in: PubMed
    Score: 0.164
  18. Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo. Crit Rev Food Sci Nutr. 2023; 63(18):3150-3167.
    View in: PubMed
    Score: 0.144
  19. Incorrect Analyses of Cluster-Randomized Trials that Do Not Take Clustering and Nesting into Account Likely Lead to p-Values that Are Too Small. Child Obes. 2020 03; 16(2):65-66.
    View in: PubMed
    Score: 0.129
  20. Observational research rigour alone does not justify causal inference. Eur J Clin Invest. 2016 Dec; 46(12):985-993.
    View in: PubMed
    Score: 0.102
  21. Regression to the Mean: A Commonly Overlooked and Misunderstood Factor Leading to Unjustified Conclusions in Pediatric Obesity Research. Child Obes. 2016 Apr; 12(2):155-8.
    View in: PubMed
    Score: 0.098
  22. Introduction to the series "Best (but Oft-Forgotten) Practices". Am J Clin Nutr. 2015 Aug; 102(2):239-40.
    View in: PubMed
    Score: 0.093
  23. Unscientific beliefs about scientific topics in nutrition. Adv Nutr. 2014 Sep; 5(5):563-5.
    View in: PubMed
    Score: 0.088
  24. Overstatement of results in the nutrition and obesity peer-reviewed literature. Am J Prev Med. 2013 Nov; 45(5):615-21.
    View in: PubMed
    Score: 0.083
  25. Association of run-in periods with weight loss in obesity randomized controlled trials. Obes Rev. 2014 Jan; 15(1):68-73.
    View in: PubMed
    Score: 0.082
  26. Misuse of odds ratios in obesity literature: an empirical analysis of published studies. Obesity (Silver Spring). 2012 Aug; 20(8):1726-31.
    View in: PubMed
    Score: 0.074
  27. Is funding source related to study reporting quality in obesity or nutrition randomized control trials in top-tier medical journals? Int J Obes (Lond). 2012 Jul; 36(7):977-81.
    View in: PubMed
    Score: 0.072
  28. Rank-based inverse normal transformations are increasingly used, but are they merited? Behav Genet. 2009 Sep; 39(5):580-95.
    View in: PubMed
    Score: 0.061
  29. Testing for differences in distribution tails to test for differences in 'maximum' lifespan. BMC Med Res Methodol. 2008 Jul 25; 8:49.
    View in: PubMed
    Score: 0.058
  30. Obesity--still highly heritable after all these years. Am J Clin Nutr. 2008 Feb; 87(2):275-6.
    View in: PubMed
    Score: 0.056
  31. Optimal allocation of replicates for measurement evaluation studies. Genomics Proteomics Bioinformatics. 2006 Aug; 4(3):196-202.
    View in: PubMed
    Score: 0.050
  32. The PowerAtlas: a power and sample size atlas for microarray experimental design and research. BMC Bioinformatics. 2006 Feb 22; 7:84.
    View in: PubMed
    Score: 0.049
  33. A design and statistical perspective on microarray gene expression studies in nutrition: the need for playful creativity and scientific hard-mindedness. Nutrition. 2003 Nov-Dec; 19(11-12):997-1000.
    View in: PubMed
    Score: 0.041
  34. Catechol-O-methyl-transferase functional polymorphism and nicotine dependence: an evaluation of nonreplicated results. Cancer Epidemiol Biomarkers Prev. 2005 Jun; 14(6):1384-9.
    View in: PubMed
    Score: 0.012
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.