Advanced search
Publication Cover
Critical Reviews in Food Science and Nutrition Volume 63, 2023 - Issue 18
Submit an article Journal homepage
8,400
Views
13
CrossRef citations to date
0
Altmetric
Review Articles

Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo

Andrew W. Browna Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USACorrespondence[email protected] [email protected]
ORCID Iconhttps://orcid.org/0000-0002-1758-8205
ORCID Icon,
Stella Aslibekyanb Department of Epidemiology, University of Alabama at Birmingham, Brimingham, Alabama, USA;;c Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, Kentucky, USA;
,
Dennis Bierd Children’s Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA;
,
Rafael Ferreira da Silvae Department of Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA;
,
Adam Hooverf Holcombe Department of Electrical and Computer Engineering, The College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, South Carolina, USA;
,
David M. Klurfeldg Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, USA;ORCID Iconhttps://orcid.org/0000-0001-7093-3998
ORCID Icon,
Eric Lokenh Department of Educational Psychology, Neag School of Education, University of Connecticut, Storrs, Connecticut, USA;
,
Evan Mayo-Wilsoni Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA;ORCID Iconhttps://orcid.org/0000-0001-6126-2459
ORCID Icon,
Nir Menachemij Department of Health Policy and Management, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, Indiana, USA;ORCID Iconhttps://orcid.org/0000-0002-3411-2700
ORCID Icon,
Greg Pavelak Department of Health Behavior, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA;
,
Patrick D. Quinna Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USAORCID Iconhttps://orcid.org/0000-0002-6770-8762
ORCID Icon,
Dale Schoellerl Department of Nutritional Sciences, University of Wisconsin-Madison Biotechnology Center, Madison, Wisconsin, USA;
,
Carmen Tekwei Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA;ORCID Iconhttps://orcid.org/0000-0002-1857-2416
ORCID Icon,
Danny Valdeza Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USAORCID Iconhttps://orcid.org/0000-0002-2355-9881
ORCID Icon,
Colby J. Vorlanda Department of Applied Health Science, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USAORCID Iconhttps://orcid.org/0000-0003-4225-372X
ORCID Icon,
Leah D. Whighamm Center for Community Health Impact and Department of Health Promotion and Behavioral Sciences, University of Texas Health Science Center School of Public Health, El Paso, Texas, USA
&
David B. Allisoni Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA;Correspondence[email protected] [email protected]
ORCID Iconhttps://orcid.org/0000-0003-3566-9399
ORCID Icon show all
Pages 3150-3167 | Published online: 22 Oct 2021

References

  • Afshari, R. 2017. Gustav III’s risk assessment on coffee consumption; A medical history report. Avicenna Journal of Phytomedicine 7 (2):99–100.
  • Almirall, D., I. Nahum-Shani, N. E. Sherwood, and S. A. Murphy. 2014. Introduction to SMART designs for the development of adaptive interventions: With application to weight loss research. Translational Behavioral Medicine 4 (3):260–74. doi: 10.1007/s13142-014-0265-0.
  • Alonso-Coello, P., A. D. Oxman, J. Moberg, R. Brignardello-Petersen, E. A. Akl, M. Davoli, S. Treweek, R. A. Mustafa, P. O. Vandvik, J. Meerpohl, et al. 2016. GRADE Evidence to Decision (EtD) frameworks: A systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines. BMJ (Clinical Research Ed.) 353:i2089. doi: 10.1136/bmj.i2089.
  • Alonso-Coello, P., H. J. Schünemann, J. Moberg, R. Brignardello-Petersen, E. A. Akl, M. Davoli, S. Treweek, R. A. Mustafa, G. Rada, S. Rosenbaum, et al. 2016. GRADE Evidence to Decision (EtD) frameworks: A systematic and transparent approach to making well informed healthcare choices. 1: Introduction. BMJ (Clinical Research Ed.) 353:i2016. doi: 10.1136/bmj.i2016.
  • Au Yeung, S. L., C. Q. Jiang, K. K. Cheng, B. Liu, W. S. Zhang, T. H. Lam, G. M. Leung, and C. M. Schooling. 2012. Evaluation of moderate alcohol use and cognitive function among men using a Mendelian randomization design in the Guangzhou biobank cohort study. American Journal of Epidemiology 175 (10):1021–8. doi: 10.1093/aje/kwr462.
  • Baker, M. 2016. 1,500 Scientists lift the lid on reproducibility. Nature 533 (7604):452–4. doi: 10.1038/533452a.
  • Barron, R., K. Bermingham, L. Brennan, E. R. Gibney, M. J. Gibney, M. F. Ryan, and A. O’Sullivan. 2016. Twin metabolomics: The key to unlocking complex phenotypes in nutrition research. Nutrition Research (New York, N.Y.) 36 (4):291–304. doi: 10.1016/j.nutres.2016.01.010.
  • Basiotis, P. P., S. O. Welsh, F. J. Cronin, J. L. Kelsay, and W. Mertz. 1987. Number of days of food intake records required to estimate individual and group nutrient intakes with defined confidence. The Journal of Nutrition 117 (9):1638–41. doi: 10.1093/jn/117.9.1638.
  • Bechhofer, S., D. De Roure, M. Gamble, C. Goble, and I. Buchan. 2010. Research objects: Towards exchange and reuse of digital knowledge. Nature Precedings 1-1. doi: 10.1038/npre.2010.4626.1.
  • Belluz, J. 2018. This Mediterranean diet study was hugely impactful. The science just fell apart. Accessed December 31, 2020. https://www.vox.com/science-and-health/2018/6/20/17464906/mediterranean-diet-science-health-predimed.
  • Blumenthal, D., E. G. Campbell, M. S. Anderson, N. Causino, and K. S. Louis. 1997. Withholding research results in academic life science. Evidence from a national survey of faculty. JAMA 277 (15):1224–8.
  • Boers, M., J. R. Kirwan, G. Wells, D. Beaton, L. Gossec, M.-A. d’Agostino, P. G. Conaghan, C. O. Bingham, P. Brooks, R. Landewé, et al. 2014. Developing core outcome measurement sets for clinical trials: OMERACT filter 2.0. Journal of Clinical Epidemiology 67 (7):745–53. doi: 10.1016/j.jclinepi.2013.11.013.
  • Brown, A. W., M. M. Bohan Brown, and D. B. Allison. 2013. Belief beyond the evidence: Using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence. The American Journal of Clinical Nutrition 98 (5):1298–308. doi: 10.3945/ajcn.113.064410.
  • Brown, A. W., J. P. Ioannidis, M. B. Cope, D. M. Bier, and D. B. Allison. 2014. Unscientific beliefs about scientific topics in nutrition. Advances in Nutrition (Bethesda, MD.) 5 (5):563–5. doi: 10.3945/an.114.006577.
  • Brown, A., K. Kaiser, and D. B. Allison. 2018. Issues with data and analyses: Errors, underlying themes, and potential solutions. Proceedings of the National Academy of Sciences of the United States of America 115 (11):2563–70. doi: 10.1073/pnas.1708279115.
  • Burrows, T. L., Y. Y. Ho, M. E. Rollo, and C. E. Collins. 2019. Validity of dietary assessment methods when compared to the method of doubly labeled water: A systematic review in adults. Frontiers in Endocrinology 10:850. doi: 10.3389/fendo.2019.00850.
  • Cade, J. E., V. J. Burley, D. L. Warm, R. L. Thompson, and B. M. Margetts. 2004. Food-frequency questionnaires: A review of their design, validation and utilisation. Nutrition Research Reviews 17 (1):5–22. doi: 10.1079/NRR200370.
  • Chalmers, I. 1990. Underreporting research is scientific misconduct. JAMA 263 (10):1405–8.
  • Chalmers, T. C., and A. S. Nadas. 1977. Randomize the first patient!. The New England Journal of Medicine 296 (2):107. doi: 10.1056/NEJM197701132960214.
  • Chan, A. W., and D. G. Altman. 2005. Identifying outcome reporting bias in randomised trials on PubMed: Review of publications and survey of authors. BMJ (Clinical Research Ed.) 330 (7494):753. doi: 10.1136/bmj.38356.424606.8F.
  • Chan, A.-W., A. Hróbjartsson, M. T. Haahr, P. C. Gøtzsche, and D. G. Altman. 2004. Empirical evidence for selective reporting of outcomes in randomized trials: Comparison of protocols to published articles. JAMA 291 (20):2457–65. doi: 10.1001/jama.291.20.2457.
  • Chan, A.-W., F. Song, A. Vickers, T. Jefferson, K. Dickersin, P. C. Gøtzsche, H. M. Krumholz, D. Ghersi, and H. B. van der Worp. 2014. Increasing value and reducing waste: Addressing inaccessible research. The Lancet 383 (9913):257–66. doi: 10.1016/S0140-6736(13)62296-5.
  • Chan, A. W., J. M. Tetzlaff, P. C. Gøtzsche, D. G. Altman, H. Mann, J. A. Berlin, K. Dickersin, A. Hróbjartsson, K. F. Schulz, W. R. Parulekar, et al. 2013. SPIRIT 2013 explanation and elaboration: Guidance for protocols of clinical trials. BMJ (Clinical Research Ed.) 346:e7586. doi: 10.1136/bmj.e7586.
  • Chin, E. L., L. Huang, Y. Y. Bouzid, C. P. Kirschke, B. Durbin-Johnson, L. M. Baldiviez, E. L. Bonnel, N. L. Keim, I. Korf, C. B. Stephensen, et al. 2019. Association of lactase persistence genotypes (rs4988235) and ethnicity with dairy intake in a healthy U.S. population. Nutrients 11 (8):1860. doi: 10.3390/nu11081860.
  • Chiu, Y.-H., J. E. Chavarro, B. A. Dickerman, J. E. Manson, K. J. Mukamal, K. M. Rexrode, E. B. Rimm, and M. A. Hernán. 2021. Estimating the effect of nutritional interventions using observational data: The American Heart Association’s 2020 Dietary Goals and mortality. American Journal of Clinical Nutrition 114 (2):690–703. doi: 10.1093/ajcn/nqab100.
  • Clark, D., R. H. Nagler, and J. Niederdeppe. 2019. Confusion and nutritional backlash from news media exposure to contradictory information about carbohydrates and dietary fats. Public Health Nutrition 22 (18):3336–48. doi: 10.1017/S1368980019002866.
  • Cofield, S. S., R. V. Corona, and, and D. B. Allison. 2010. Use of causal language in observational studies of obesity and nutrition. Obesity Facts 3 (6):353–6. doi: 10.1159/000322940.
  • Colen, C. G., and D. M. Ramey. 2014. Is breast truly best? Estimating the effects of breastfeeding on long-term child health and wellbeing in the United States using sibling comparisons. Social Science & Medicine (1982) 109:55–65. doi: 10.1016/j.socscimed.2014.01.027.
  • Collins, L. M. 2018. Optimization of behavioral, biobehavioral, and biomedical interventions: The multiphase optimization strategy (MOST). Cham, Switzerland: Springer International Publishing.
  • Cooper, H., K. DeNeve, and K. Charlton. 1997. Finding the missing science: The fate of studies submitted for review by a human subjects committee. Psychological Methods 2 (4):447–52. doi: 10.1037/1082-989X.2.4.447.
  • Cybulski, L., E. Mayo-Wilson, and S. Grant. 2016. Improving transparency and reproducibility through registration: The status of intervention trials published in clinical psychology journals. The Journal of Consulting and Clinical Psychology 84 (9):753–67. doi: 10.1037/ccp0000115.
  • D’Onofrio, B. M., Q. A. Class, M. E. Rickert, A. C. Sujan, H. Larsson, R. Kuja-Halkola, A. Sjölander, C. Almqvist, P. Lichtenstein, A. S. Oberg, et al. 2016. Translational epidemiologic approaches to understanding the consequences of early-life exposures. Behavior Genetics 46 (3):315–28. doi: 10.1007/s10519-015-9769-8.
  • Davey Smith, G., and S. Ebrahim. 2003. Mendelian randomization: Can genetic epidemiology contribute to understanding environmental determinants of disease? International Journal of Epidemiology 32 (1):1–22. doi: 10.1093/ije/dyg070.
  • De Angelis, C. D., J. M. Drazen, F. A. Frizelle, C. Haug, J. Hoey, R. Horton, S. Kotzin, C. Laine, A. Marusic, A. J. P. M. Overbeke, et al. 2005. Is this clinical trial fully registered? A statement from the International Committee of Medical Journal Editors Annals of Internal Medicine 143 (2):146–8. doi: 10.7326/0003-4819-143-2-200507190-00016.
  • De Angelis, C., J. M. Drazen, F. A. Frizelle, C. Haug, J. Hoey, R. Horton, S. Kotzin, C. Laine, A. Marusic, A. J. P. M. Overbeke, et al. 2004. Clinical trial registration: A statement from the international committee of medical journal editors. The New England Journal of Medicine 351 (12):1250–1. doi: 10.1056/NEJMe048225.
  • Deelman, E., K. Vahi, G. Juve, M. Rynge, S. Callaghan, P. J. Maechling, R. Mayani, W. Chen, R. Ferreira da Silva, M. Livny, et al. 2015. Pegasus, a workflow management system for science automation. Future Generation Computer Systems 46:17–35. doi: 10.1016/j.future.2014.10.008.
  • Dhurandhar, N. V., D. Schoeller, A. W. Brown, S. B. Heymsfield, D. Thomas, T. I. Sørensen, J. R. Speakman, M. Jeansonne, and D. B. Allison. 2015. Energy balance measurement: When something is not better than nothing. International Journal of Obesity (2005) 39 (7):1109–13. doi: 10.1038/ijo.2014.199.
  • Dickersin, K. 1990. The existence of publication bias and risk factors for its occurrence. JAMA 263 (10):1385–9. doi: 10.1001/jama.1990.03440100097014.
  • Dickersin, K., and E. Mayo-Wilson. 2018. Standards for design and measurement would make clinical research reproducible and usable. Proceedings of the National Academy of Sciences of the United States of America 115 (11):2590–4. doi: 10.1073/pnas.1708273114.
  • Duan, N., R. L. Kravitz, and C. H. Schmid. 2013. Single-patient (n-of-1) trials: A pragmatic clinical decision methodology for patient-centered comparative effectiveness research. Journal of Clinical Epidemiology 66 (8 Suppl):S21–S8.
  • Dwan, K., C. Gamble, P. R. Williamson, and J. J. Kirkham. 2013. Systematic review of the empirical evidence of study publication bias and outcome reporting bias - An updated review. PLoS One 8 (7):e66844. doi: 10.1371/journal.pone.0066844.
  • Ejima, K., A. W. Brown, D. A. Schoeller, S. B. Heymsfield, E. J. Nelson, and D. B. Allison. 2019. Does exclusion of extreme reporters of energy intake (the “Goldberg cutoffs”) reliably reduce or eliminate bias in nutrition studies? Analysis with illustrative associations of energy intake with health outcomes. American Journal of Clinical Nutrition 110 (5):1231–9. doi: 10.1093/ajcn/nqz198.
  • Ferdinand, O. A., B. Sen, S. Rahurkar, S. Engler, and N. Menachemi. 2012. The relationship between built environments and physical activity: A systematic review. American Journal of Public Health 102 (10):e7–13.
  • Fontana, J. M., J. A. Higgins, S. C. Schuckers, F. Bellisle, Z. Pan, E. L. Melanson, M. R. Neuman, and E. Sazonov. 2015. Energy intake estimation from counts of chews and swallows. Appetite 85:14–21. doi: 10.1016/j.appet.2014.11.003.
  • Forbes, G. B. 1984. Energy intake and body weight: A reexamination of two “classic” studies. The American Journal of Clinical Nutrition 39 (3):349–50. doi: 10.1093/ajcn/39.3.349.
  • Franco, A., N. Malhotra, and G. Simonovits. 2014. Social science. Publication bias in the social sciences: Unlocking the file drawer. Science (New York, N.Y.) 345 (6203):1502–5. doi: 10.1126/science.1255484.
  • Friedman, L. M., C. Furberg, D. L. DeMets, D. M. Reboussin, and C. B. Granger. 2010. Fundamentals of clinical trials. New York: Springer.
  • Frisell, T., S. Öberg, R. Kuja-Halkola, and A. Sjölander. 2012. Sibling comparison designs: Bias from non-shared confounders and measurement error. Epidemiology (Cambridge, Mass.) 23 (5):713–20. doi: 10.1097/EDE.0b013e31825fa230.
  • Gamble, C., A. Krishan, D. Stocken, S. Lewis, E. Juszczak, C. Doré, P. R. Williamson, D. G. Altman, A. Montgomery, P. Lim, et al. 2017. Guidelines for the content of statistical analysis plans in clinical trials. JAMA 318 (23):2337–43. doi: 10.1001/jama.2017.18556.
  • Ge, L., B. Sadeghirad, G. D. C. Ball, B. R. da Costa, C. L. Hitchcock, A. Svendrovski, R. Kiflen, K. Quadri, H. Y. Kwon, M. Karamouzian, et al. 2020. Comparison of dietary macronutrient patterns of 14 popular named dietary programmes for weight and cardiovascular risk factor reduction in adults: Systematic review and network meta-analysis of randomised trials. BMJ 369:m696. doi: 10.1136/bmj.m696.
  • Gelman, A., and E. Loken. 2001. The garden of forking paths: Why multiple comparisons can be a problem, even when there is no “fishing expedition” or “p-hacking” and the research hypothesis was posited ahead of time. Last Modified November 14, 2013. Accessed October 6, 2021. http://www.stat.columbia.edu/∼gelman/research/unpublished/forking.pdf.
  • George, B. J., P. Li, H. R. Lieberman, G. Pavela, A. W. Brown, K. R. Fontaine, M. M. Jeansonne, G. R. Dutton, A. J. Idigo, M. A. Parman, et al. 2018. Randomization to randomization probability: Estimating treatment effects under actual conditions of use. Psychological Methods 23 (2):337–50. doi: 10.1037/met0000138.
  • Goble, C. A., J. Bhagat, S. Aleksejevs, D. Cruickshank, D. Michaelides, D. Newman, M. Borkum, S. Bechhofer, M. Roos, P. Li, et al. 2010. myExperiment: A repository and social network for the sharing of bioinformatics workflows. Nucleic Acids Research 38 (Web Server issue):W677–82. doi: 10.1093/nar/gkq429.
  • Goldenberg, J. Z., D. Mertz, and B. C. Johnston. 2018. Probiotics to prevent Clostridium difficile infection in patients receiving antibiotics. JAMA 320 (5):499–500. doi: 10.1001/jama.2018.9064.
  • Goldsby, T., B. George, V. Yeager, B. Sen, A. Ferdinand, D. Sims, B. Manzella, A. Cockrell Skinner, D. Allison, and N. Menachemi. 2016. Urban park development and pediatric obesity rates: A quasi-experiment using electronic health record data. International Journal of Environmental Research and Public Health 13 (4):411. doi: 10.3390/ijerph13040411.
  • Goodman, S., and K. Dickersin. 2011. Metabias: A challenge for comparative effectiveness research. Annals of Internal Medicine 155 (1):61–2. doi: 10.7326/0003-4819-155-1-201107050-00010.
  • Goodman, S., D. Fanelli, and J. P. Ioannidis. 2016. What does research reproducibility mean? Science Translational Medicine 8 (341):341ps12. doi: 10.1126/scitranslmed.aaf5027.
  • Granic, A., R. Andel, A. K. Dahl, M. Gatz, and N. L. Pedersen. 2013. Midlife dietary patterns and mortality in the population-based study of Swedish twins. Journal of Epidemiology and Community Health 67 (7):578–86. doi: 10.1136/jech-2012-201780.
  • Greenland, S. 2008. Invited commentary: Variable selection versus shrinkage in the control of multiple confounders. American Journal of Epidemiology 167 (5):523–9. doi: 10.1093/aje/kwm355.
  • Guyatt, G., G. Vist, Y. Falck-Ytter, R. Kunz, N. Magrini, and H. Schunemann. 2006. An emerging consensus on grading recommendations? Evidence-Based Medicine 11 (1):2–4. doi: 10.1136/ebm.11.1.2-a.
  • Haber, N., E. R. Smith, E. Moscoe, K. Andrews, R. Audy, W. Bell, A. T. Brennan, A. Breskin, J. C. Kane, M. Karra, et al. 2018. Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review. PloS One 13 (5):e0196346. doi: 10.1371/journal.pone.0196346.
  • Hahn, S., P. R. Williamson, and J. L. Hutton. 2002. Investigation of within-study selective reporting in clinical research: Follow-up of applications submitted to a local research ethics committee. Journal of Evaluation in Clinical Practice 8 (3):353–9. doi: 10.1046/j.1365-2753.2002.00314.x.
  • Haycock, P. C., S. Burgess, K. H. Wade, J. Bowden, C. Relton, and G. Davey Smith. 2016. Best (but oft-forgotten) practices: The design, analysis, and interpretation of Mendelian randomization studies. The American Journal of Clinical Nutrition 103 (4):965–78. doi: 10.3945/ajcn.115.118216.
  • Hayes, M. J., V. Kaestner, S. Mailankody, and V. Prasad. 2018. Most medical practices are not parachutes: A citation analysis of practices felt by biomedical authors to be analogous to parachutes. CMAJ Open 6 (1):E31–8. doi: 10.9778/cmajo.20170088.
  • Hébert, J. R., E. A. Frongillo, S. A. Adams, G. M. Turner-McGrievy, T. G. Hurley, D. R. Miller, and I. S. Ockene. 2016. Perspective: Randomized controlled trials are not a panacea for diet-related research. Advances in Nutrition (Bethesda, MD.) 7 (3):423–32. doi: 10.3945/an.115.011023.
  • Hemming, K., T. P. Haines, P. J. Chilton, A. J. Girling, and R. J. Lilford. 2015. The stepped wedge cluster randomised trial: Rationale, design, analysis, and reporting. BMJ (Clinical Research Ed.) 350:h391. doi: 10.1136/bmj.h391.
  • Hernán, M. A. 2018. The C-word: Scientific euphemisms do not improve causal inference from observational data. American Journal of Public Health 108 (5):616–9. doi: 10.2105/AJPH.2018.304337.
  • Hill, A. B. 1965. The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine 58 (5):295–300.
  • Hoover, A., and E. Sazonov. 2016. Measuring human energy intake and ingestive behavior: Challenges and opportunities. IEEE Pulse. 7 (6):6–7. doi: 10.1109/MPUL.2016.2606465.
  • Huo, D., J. Nabrzyski, and C. F. VardemanII. 2015. An ontology design pattern towards preservation of computational experiments. Bethlehem, PA: Proceedings of the 5th Workshop on Linked Science.
  • Imbens, G. W., and D. B. Rubin. 2015. Causal inference in statistics, social, and biomedical sciences. Cambridge, UK: Cambridge University Press.
  • Ioannidis, J. P. A., and J. F. Trepanowski. 2018. Disclosures in nutrition research: Why it is different. JAMA 319 (6):547–8. doi: 10.1001/jama.2017.18571.
  • Jepsen, P., S. P. Johnsen, M. W. Gillman, and H. T. Sørensen. 2004. Interpretation of observational studies. Heart (British Cardiac Society) 90 (8):956–60. doi: 10.1136/hrt.2003.017269.
  • Johnston, B. C., P. Alonso-Coello, M. M. Bala, D. Zeraatkar, M. Rabassa, C. Valli, C. Marshall, R. El Dib, R. W. Vernooij, P. O. Vandvik, et al. 2018. Methods for trustworthy nutritional recommendations NutriRECS (Nutritional Recommendations and accessible Evidence summaries Composed of Systematic reviews): A protocol. BMC Medical Research Methodology 18 (1):1–11. doi: 10.1186/s12874-018-0621-8.
  • Johnston, B. C., D. Zeraatkar, M. A. Han, R. W. M. Vernooij, C. Valli, R. El Dib, C. Marshall, P. J. Stover, S. Fairweather-Taitt, G. Wójcik, et al. 2019. Unprocessed red meat and processed meat consumption: Dietary guideline recommendations from the Nutritional Recommendations (NutriRECS) Consortium. Annals of Internal Medicine 171 (10):756–64. doi: 10.7326/M19-1621.
  • Kaprio, J., and M. Koskenvuo. 1989. Twins, smoking and mortality: A 12-year prospective study of smoking-discordant twin pairs. Social Science & Medicine (1982) 29 (9):1083–9. doi: 10.1016/0277-9536(89)90020-8.
  • Katz, D. L. 2019. Science advisory: Children should keep running with scissors! (except, of course, not really) Accessed January 13, 2021. https://www.linkedin.com/pulse/science-advisory-children-should-keep-running-except-david/.
  • Katz, D. L., M. C. Karlsen, M. Chung, M. M. Shams-White, L. W. Green, J. Fielding, A. Saito, and W. Willett. 2019. Hierarchies of evidence applied to lifestyle Medicine (HEALM): Introduction of a strength-of-evidence approach based on a methodological systematic review. BMC Medical Research Methodology 19 (1):178. doi: 10.1186/s12874-019-0811-z.
  • Kerr, N. L. 1998. HARKing: Hypothesizing after the results are known. Personality and Social Psychology Review: An Official Journal of the Society for Personality and Social Psychology, Inc 2 (3):196–217. doi: 10.1207/s15327957pspr0203_4.
  • Kim, S. Y., J. Flory, and C. Relton. 2018. Ethics and practice of trials within cohorts: An emerging pragmatic trial design. Clinical Trials (London, England) 15 (1):9–16. doi: 10.1177/1740774517746620.
  • Kipnis, V., D. Midthune, L. Freedman, S. Bingham, N. E. Day, E. Riboli, P. Ferrari, and R. J. Carroll. 2002. Bias in dietary-report instruments and its implications for nutritional epidemiology. Public Health Nutrition 5 (6A):915–23. doi: 10.1079/PHN2002383.
  • Kitzes, J., D. Turek, and F. Deniz, eds. 2017. The practice of reproducible research: Case studies and lessons from the data-intensive sciences. Berkeley, CA: University of California Press.
  • Klimentov, A., P. Buncic, K. De, S. Jha, T. Maeno, R. Mount, P. Nilsson, D. Oleynik, S. Panitkin, A. Petrosyan, et al. 2015. Next generation workload management system for big data on heterogeneous distributed computing. Journal of Physics: Conference Series 608 (1):012040. doi: 10.1088/1742-6596/608/1/012040.
  • Klurfeld, D. M. 2015. Research gaps in evaluating the relationship of meat and health. Meat Science 109:86–95. doi: 10.1016/j.meatsci.2015.05.022.
  • Krall, E. A., and J. T. Dwyer. 1987. Validity of a food frequency questionnaire and a food diary in a short-term recall situation. Journal of the American Dietetic Association 87 (10):1374–7. doi: 10.1016/S0002-8223(21)03325-3.
  • Lear, S. 2019. Should you eat red meat? Navigating a world of contradicting studies. Accessed December 31, 2020. https://www.discovermagazine.com/health/should-you-eat-red-meat-navigating-a-world-of-contradicting-studies#.XaM8HPlKiMo.
  • Lei, H., I. Nahum-Shani, K. Lynch, D. Oslin, and S. A. Murphy. 2012. A “SMART” design for building individualized treatment sequences. Annual Review of Clinical Psychology 8:21–48.
  • Leigh, A. 2018. Randomistas: How radical researchers are changing our world. New Haven, CT: Yale University Press.
  • Leroy, F., and N. D. Barnard. 2020. Children and adults should avoid consuming animal products to reduce risk for chronic disease: NO. American Journal of Clinical Nutrition 112 (4):931–6. doi: 10.1093/ajcn/nqaa236.
  • Lichtenstein, P., U. De Faire, B. Floderus, M. Svartengren, P. Svedberg, and N. L. Pedersen. 2002. The Swedish Twin Registry: A unique resource for clinical, epidemiological and genetic studies. Journal of Internal Medicine 252 (3):184–205. doi: 10.1046/j.1365-2796.2002.01032.x.
  • MacLean, P. S., Rothman, A. J. Nicastro, H. L. Czajkowski, S. M. Agurs‐Collins, T. Rice, E. L. Courcoulas, A. P. Ryan, D. H. Bessesen, and D. H. Loria. 2018. The accumulating data to optimally predict obesity treatment (ADOPT) core measures project: Rationale and approach. Obesity 26:S6–S15. doi: 10.1002/oby.22154.
  • Mayo-Wilson, E., N. Fusco, T. Li, H. Hong, J. K. Canner, and K. Dickersin. 2017. Multiple outcomes and analyses in clinical trials create challenges for interpretation and research synthesis. Journal of Clinical Epidemiology 86:39–50. doi: 10.1016/j.jclinepi.2017.05.007.
  • Mayo-Wilson, E., J. Heyward, A. Keyes, J. Reynolds, S. White, N. Atri, G. C. Alexander, A. Omar, and D. E. Ford. 2018. Clinical trial registration and reporting: A survey of academic organizations in the United States. BMC Medicine 16 (1):60. doi: 10.1186/s12916-018-1042-6.
  • Mayo-Wilson, E., T. Li, N. Fusco, L. Bertizzolo, J. K. Canner, T. Cowley, P. Doshi, J. Ehmsen, G. Gresham, N. Guo, et al. 2017. Cherry-picking by trialists and meta-analysts can drive conclusions about intervention efficacy. Journal of Clinical Epidemiology 91:95–110. doi: 10.1016/j.jclinepi.2017.07.014.
  • Mayo-Wilson, E., T. Li, N. Fusco, and K. Dickersin. 2018. Practical guidance for using multiple data sources in systematic reviews and meta-analyses (with examples from the MUDS study). Research Synthesis Methods 9 (1):2–12. doi: 10.1002/jrsm.1277.
  • McGue, M., M. Osler, and K. Christensen. 2010. Causal inference and observational research: The utility of twins. Perspectives on Psychological Science: A Journal of the Association for Psychological Science 5 (5):546–56. doi: 10.1177/1745691610383511.
  • Meerpohl, J. J., C. E. Naude, P. Garner, R. A. Mustafa, and H. J. Schünemann. 2017. Comment on “Perspective: NutriGrade: A scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition Research.” Advances in Nutrition (Bethesda, MD.) 8 (5):789–90. doi: 10.3945/an.117.016188.
  • Meinert, C. 1986. Clinical trials - Design, conduct, and analysis. New York: Oxford University Press.
  • Meinert, C. L. 1988. Toward prospective registration of clinical trials. Controlled Clinical Trials 9 (1):1–5. doi: 10.1016/0197-2456(88)90002-5.
  • Mendelian Randomization of Dairy Consumption Working Group. 2018. Dairy consumption and body mass index among adults: Mendelian randomization analysis of 184802 individuals from 25 studies. Clinical Chemistry 64 (1):183–91.
  • Metzger, M. W., and T. W. McDade. 2010. Breastfeeding as obesity prevention in the United States: A sibling difference model. American Journal of Human Biology: The Official Journal of the Human Biology Council 22 (3):291–6. doi: 10.1002/ajhb.20982.
  • Mills, J. L. 1993. Data torturing. The New England Journal of Medicine 329 (16):1196–9. doi: 10.1056/NEJM199310143291613.
  • Molenaar, P. C. 2004. A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement 2 (4):201–18.
  • Morgan, S. L., and C. Winship. 2015. Counterfactuals and causal inference. Cambridge, UK: Cambridge University Press.
  • Moshfegh, A. J., D. G. Rhodes, D. J. Baer, T. Murayi, J. C. Clemens, W. V. Rumpler, D. R. Paul, R. S. Sebastian, K. J. Kuczynski, L. A. Ingwersen, et al. 2008. The US Department of Agriculture automated multiple-pass method reduces bias in the collection of energy intakes. The American Journal of Clinical Nutrition 88 (2):324–32. doi: 10.1093/ajcn/88.2.324.
  • National Academies of Sciences, Engineering, and Medicine. 2019. Reproducibility and replicability in science. Washington, DC: National Academies Press.
  • Naukkarinen, J., A. Rissanen, J. Kaprio, and K. H. Pietiläinen. 2012. Causes and consequences of obesity: The contribution of recent twin studies. International Journal of Obesity (2005) 36 (8):1017–24. doi: 10.1038/ijo.2011.192.
  • Neuhouser, M. L. 2020. Red and processed meat: More with less? The American Journal of Clinical Nutrition 111 (2):252–5. doi: 10.1093/ajcn/nqz294.
  • Nosek, B. A., G. Alter, G. C. Banks, D. Borsboom, S. D. Bowman, S. J. Breckler, S. Buck, C. D. Chambers, G. Chin, G. Christensen, et al. 2015. Scientific standards. Promoting an open research culture. Science (New York, N.Y.) 348 (6242):1422–5. doi: 10.1126/science.aab2374.
  • Nosek, B. A., C. R. Ebersole, A. C. DeHaven, and D. T. Mellor. 2018. The preregistration revolution. Proceedings of the National Academy of Sciences of the United States of America 115 (11):2600–6. doi: 10.1073/pnas.1708274114.
  • Nüst, D., M. Konkol, E. Pebesma, C. Kray, M. Schutzeichel, H. Przibytzin, and J. Lorenz. 2017. Opening the publication process with executable research compendia. D-Lib Magazine 23 (1/2):10–1045. doi: 10.1045/january2017-nuest.
  • Open Science Collaboration. 2015. Estimating the reproducibility of psychological science. Science 349 (6251):aac4716. doi: 10.1126/science.aac4716
  • Oreskes, N. 2021. So is it okay to eat more red and processed meat? Accessed January 13, 2021. https://www.scientificamerican.com/article/so-is-it-okay-to-eat-more-red-and-processed-meat/.
  • Pallister, T., T. D. Spector, and C. Menni. 2014. Twin studies advance the understanding of gene-environment interplay in human nutrigenomics. Nutrition Research Reviews 27 (2):242–51. doi: 10.1017/S095442241400016X.
  • Patel, C. J., and J. P. Ioannidis. 2014. Placing epidemiological results in the context of multiplicity and typical correlations of exposures. Journal of Epidemiology and Community Health 68 (11):1096–100. doi: 10.1136/jech-2014-204195.
  • Patel, C. J., B. Burford, and J. P. Ioannidis. 2015. Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations. Journal of Clinical Epidemiology 68 (9):1046–58. doi: 10.1016/j.jclinepi.2015.05.029.
  • Pavela, G., H. Wiener, K. R. Fontaine, D. A. Fields, J. D. Voss, and D. B. Allison. 2015. Packet randomized experiments for eliminating classes of confounders. European Journal of Clinical Investigation 45 (1):45–55. doi: 10.1111/eci.12378.
  • Pc, K. J. K., A. Hróbjartsson, H. Mann, K. Dickersin, J. Berlin, C. Doré, and H. Sox. 2010. A catalogue of reporting guidelines for health research. BMC Medicine 8 (18):20334633.
  • Prentice, A. M., A. E. Black, W. A. Coward, H. L. Davies, G. R. Goldberg, P. R. Murgatroyd, J. Ashford, M. Sawyer, and R. G. Whitehead. 1986. High levels of energy expenditure in obese women. British Medical Journal (Clinical Research Ed.) 292 (6526):983–7. doi: 10.1136/bmj.292.6526.983.
  • Qian, F., M. C. Riddle, J. Wylie-Rosett, and F. B. Hu. 2020. Red and processed meats and health risks: How strong is the evidence? Diabetes Care 43 (2):265–71. doi: 10.2337/dci19-0063.
  • Rhodes, D. G., T. Murayi, J. C. Clemens, D. J. Baer, R. S. Sebastian, and A. J. Moshfegh. 2013. The USDA automated multiple-pass method accurately assesses population sodium intakes. The American Journal of Clinical Nutrition 97 (5):958–64. doi: 10.3945/ajcn.112.044982.
  • Rice, D. B., and D. Moher. 2019. Curtailing the use of preregistration: A misused term. Perspectives on Psychological Science: A Journal of the Association for Psychological Science 14 (6):1105–8. doi: 10.1177/1745691619858427.
  • Richardson, M. B., M. S. Williams, K. R. Fontaine, and D. B. Allison. 2017. The development of scientific evidence for health policies for obesity: Why and how? International Journal of Obesity (2005) 41 (6):840–8. doi: 10.1038/ijo.2017.71.
  • Ritchie, S. 2020. Science fictions: How fraud, bias, negligence, and hype undermine the search for truth. New York, NY: Metropolitan Books.
  • Rosenbaum, P. R., and D. B. Rubin. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70 (1):41–55. doi: 10.1093/biomet/70.1.41.
  • Rosenthal, R. 1979. The file drawer problem and tolerance for null results. Psychological Bulletin 86 (3):638–41. doi: 10.1037/0033-2909.86.3.638.
  • Rubin, R. 2020. Backlash over meat dietary recommendations raises questions about corporate ties to nutrition scientists. JAMA 323 (5):401–4. doi: 10.1001/jama.2019.21441.
  • Sacristán, J. A., and T. Dilla. 2018. Pragmatic trials revisited: Applicability is about individualization. Journal of Clinical Epidemiology 99:164–6. doi: 10.1016/j.jclinepi.2018.02.003.
  • Salley, J., E. Muth, M. Wilson, and A. Hoover. 2016. A comparison between human and bite-based methods of estimating caloric intake. Journal of the Academy of Nutrition and Dietetics 116 (10):1568–77. doi: 10.1016/j.jand.2016.03.007.
  • Satija, A., E. Yu, W. C. Willett, and F. B. Hu. 2015. Understanding nutritional epidemiology and its role in policy. Advances in Nutrition (Bethesda, MD.) 6 (1):5–18. doi: 10.3945/an.114.007492.
  • Schoeller, D.A., and M. Westerterp, eds. 2017. Advances in the assessment of dietary intake. Boca Raton, FL: CRC Press.
  • Schuemie, M. J., P. B. Ryan, W. DuMouchel, M. A. Suchard, and D. Madigan. 2014. Interpreting observational studies: Why empirical calibration is needed to correct p‐values. Statistics in Medicine 33 (2):209–18. doi: 10.1002/sim.5925.
  • Schwingshackl, L., S. Knüppel, C. Schwedhelm, G. Hoffmann, B. Missbach, M. Stelmach-Mardas, S. Dietrich, F. Eichelmann, E. Kontopantelis, K. Iqbal, et al. 2016. Perspective: NutriGrade: A scoring system to assess and judge the meta-evidence of randomized controlled trials and cohort studies in nutrition research. Advances in Nutrition (Bethesda, MD.) 7 (6):994–1004. doi: 10.3945/an.116.013052.
  • Schwingshackl, L., S. Knüppel, C. Schwedhelm, G. Hoffmann, B. Missbach, M. Stelmach-Mardas, S. Dietrich, F. Eichelmann, E. Kontopantelis, K. Iqbal, et al. 2017. Reply to JJ Meerpohl et al. Advances in Nutrition (Bethesda, MD.) 8 (5):790–1. doi: 10.3945/an.117.016469.
  • Scisco, J., E. Muth, and A. Hoover. 2014. Examining the utility of a bite-count based measure of eating activity in free-living human beings. Journal of the Academy of Nutrition and Dietetics 114 (3):464–9. doi: 10.1016/j.jand.2013.09.017.
  • Selvaraj, S., D. S. Borkar, and V. Prasad. 2014. Media coverage of medical journals: Do the best articles make the news? PLoS One 9 (1):e85355. doi: 10.1371/journal.pone.0085355.
  • Shadish, W. R., D. T. Campbell, and T. D. Cook. 2001. Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin.
  • Simes, R. J. 1986. Publication bias: The case for an international registry of clinical trials. Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology 4 (10):1529–41. doi: 10.1200/JCO.1986.4.10.1529.
  • Simmons, J. P., L. D. Nelson, and U. Simonsohn. 2011. False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science 22 (11):1359–66. doi: 10.1177/0956797611417632.
  • Simonsohn, U., J. P. Simmons, and L. D. Nelson. 2019. Specification curve: Descriptive and inferential statistics on all reasonable specifications. Available at SSRN 2694998. doi: 10.2139/ssrn.2694998.
  • Simonsohn, U., J. P. Simmons, and L. D. Nelson. 2020. Specification curve analysis. Nature Human Behaviour 4 (11):1208–14. doi: 10.1038/s41562-020-0912-z.
  • Speakman, J. R., Y. Yamada, H. Sagayama, E. S. F. Berman, P. N. Ainslie, L. F. Andersen, L. J. Anderson, L. Arab, I. Baddou, K. Bedu-Addo, et al. 2021. A standard calculation methodology for human doubly labeled water studies. Cell Reports Medicine 2 (2):100203. doi: 10.1016/j.xcrm.2021.100203.
  • Steegen, S., F. Tuerlinckx, A. Gelman, and W. Vanpaemel. 2016. Increasing transparency through a multiverse analysis. Perspectives on Psychological Science: A Journal of the Association for Psychological Science 11 (5):702–12. doi: 10.1177/1745691616658637.
  • Stodden, V., C. Hurlin, and C. Pérignon. 2012. RunMyCode.org: A novel dissemination and collaboration platform for executing published computational results, 1–8. Chicago, IL: 2012 IEEE 8th International Conference on E-Science
  • Subar, A. F., S. I. Kirkpatrick, B. Mittl, T. P. Zimmerman, F. E. Thompson, C. Bingley, G. Willis, N. G. Islam, T. Baranowski, S. McNutt, et al. 2012. The Automated Self-Administered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the National Cancer Institute. Journal of the Academy of Nutrition and Dietetics 112 (8):1134–7. doi: 10.1016/j.jand.2012.04.016.
  • Sweedler, J. V. 2019. Reproducibility and replicability. Analytical Chemistry 91 (13):7971–2. doi: 10.1021/acs.analchem.9b02719.
  • Tannock, I. F. 1996. False-positive results in clinical trials: Multiple significance tests and the problem of unreported comparisons. Journal of the National Cancer Institute 88 (3–4):206–7. doi: 10.1093/jnci/88.3-4.206.
  • Te Morenga, L., S. Mallard, and J. Mann. 2012. Dietary sugars and body weight: Systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ 346 (3):e7492–e7492. doi: 10.1136/bmj.e7492.
  • Teicholz, N., and G. Taubes. 2018. Rapid response to: Dietary guidelines and health—Is nutrition science up to the task? Accessed December 31, 2020. https://www.bmj.com/content/360/bmj.k822/rr-13.
  • Tekwe, C. D., R. S. Zoh, M. Yang, R. J. Carroll, G. Honvoh, D. B. Allison, M. Benden, and L. Xue. 2019. Instrumental variable approach to estimating the scalar-on-function regression model with measurement error with application to energy expenditure assessment in childhood obesity. Statistics in Medicine 38 (20):3764–81. doi: 10.1002/sim.8179.
  • Tobias, D. K., and M. Lajous. 2021. What would the trial be? Emulating randomized dietary intervention trials to estimate causal effects with observational data. The American Journal of Clinical Nutrition 114 (2):416–7. doi: 10.1093/ajcn/nqab169.
  • Trepanowski, J. F., and J. P. A. Ioannidis, 2018. Perspective: Limiting dependence on nonrandomized studies and improving randomized trials in human nutrition research: Why and how. Advances in Nutrition (Bethesda, MD.) 9 (4):367–77. doi: 10.1093/advances/nmy014.
  • Vernooij, R. W. M., G. H. Guyatt, D. Zeraatkar, M. A. Han, C. Valli, R. El Dib, P. Alonso-Coello, M. M. Bala, and B. C. Johnston, 2021. Reconciling contrasting guideline recommendations on red and processed meat for health outcomes. Journal of Clinical Epidemiology S0895–4356 (21): 00216-X. doi: 10.1016/j.jclinepi.2021.07.008 Online ahead of print
  • Vissers, L. E. T., I. Sluijs, Y. T. van der Schouw, N. G. Forouhi, F. Imamura, S. Burgess, A. Barricarte, H. Boeing, C. Bonet, M.-D. Chirlaque, et al. 2019. Dairy product intake and risk of type 2 diabetes in EPIC-InterAct: A Mendelian randomization study. Diabetes Care 42 (4):568–75. doi: 10.2337/dc18-2034.
  • Walker, J. L., S. Ardouin, and T. Burrows, 2018. The validity of dietary assessment methods to accurately measure energy intake in children and adolescents who are overweight or obese: A systematic review. European Journal of Clinical Nutrition 72 (2):185–97. doi: 10.1038/s41430-017-0029-2.
  • Wallach, J. D., and H. M. Krumholz, 2019. Not reporting results of a clinical trial is academic misconduct. Annals of Internal Medicine 171 (4):293–4. doi: 10.7326/M19-1273. [published Online First: 2019/05/07]
  • Wang, M. Q., A. F. Yan, and R. V. Katz, 2018. Researcher requests for inappropriate analysis and reporting: A US survey of consulting biostatisticians. Annals of Internal Medicine 169 (8):554–8. doi: 10.7326/M18-1230. [published Online First: 2018/10/12]
  • Weathers, D., J. Siemens, and S. Kopp, 2017. Tracking food intake as bites: Effects on cognitive resources, eating enjoyment, and self-control. Appetite 111:23–31. doi: 10.1016/j.appet.2016.12.018.
  • Westfall, J., and T. Yarkoni, 2016. Statistically controlling for confounding constructs is harder than you think. PLoS One 11 (3):e0152719. doi: 10.1371/journal.pone.0152719.
  • Williams, R. J., T. Tse, W. R. Harlan, and D. A. Zarin. 2010. Registration of observational studies: Is it time? CMAJ: Canadian Medical Association Journal = Journal de L’Association Medicale Canadienne 182 (15):1638–42. doi: 10.1503/cmaj092252.
  • Williamson, P. R., and C. Gamble, 2005. Identification and impact of outcome selection bias in meta-analysis. Statistics in Medicine 24 (10):1547–61. doi: 10.1002/sim.2025.
  • Williamson, P. R., C. Gamble, D. G. Altman, and J. L. Hutton, 2005. Outcome selection bias in meta-analysis. Statistical Methods in Medical Research 14 (5):515–24. doi: 10.1191/0962280205sm415oa. [published Online First: 2005/10/27]
  • Willett, W. C., R. D. Reynolds, S. Cottrell-Hoehner, L. Sampson, and M. L. Browne, 1987. Validation of a semi-quantitative food frequency questionnaire: Comparison with a 1-year diet record. Journal of the American Dietetic Association 87 (1):43–7. doi: 10.1016/S0002-8223(21)03057-1.
  • Windsor, R., T. Baranowski, G. Cutter, and R. A. Windsor. 2001. Evaluation of health promotion, health education, and disease prevention programs with PowerWeb. New York, NY: McGraw-Hill Higher Education.
  • Winter-Jensen, M., S. Afzal, T. Jess, B. G. Nordestgaard, and K. H. Allin, 2020. Body mass index and risk of infections: A Mendelian randomization study of 101,447 individuals. European Journal of Epidemiology 35 (4):347–54. doi: 10.1007/s10654-020-00630-7.
  • World Medical Association. 2001. World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects. Bulletin of the World Health Organization 79 (4):373–4.
  • Zarin, D. A., T. Tse, R. J. Williams, R. M. Califf, and N. C. Ide, 2011. The ClinicalTrials.gov results database-update and key issues. The New England Journal of Medicine 364 (9):852–60. doi: 10.1056/NEJMsa1012065.
  • Zarin, D. A., T. Tse, R. J. Williams, and T. Rajakannan, 2017. Update on trial registration 11 years after the ICMJE policy was established. The New England Journal of Medicine 376 (4):383–91. doi: 10.1056/NEJMsr1601330.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.