Review Articles

On the formation and use of calibration equations in nutritional epidemiology – Discussion of the Paper by R. L. Prentice and Y. Huang

Laurence S. Freedman ,

Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, Israel

Pamela A. Shaw

Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Pages 11-13 | Received 29 May. 2018, Accepted 23 Jun. 2018, Published online: 19 Jun. 2018,
  • Abstract
  • Full Article
  • References
  • Citations


  1. Ala-Korpela, M. (2018). Objective metabolomics research. Clinical Chemistry, 64(1), 3033. doi: 10.1373/clinchem.2017.274852 [Google Scholar]
  2. Carroll, R. J. (2014). Estimating the distribution of dietary consumption patterns. Statistical Science, 29(1), 28. doi: 10.1214/12-STS413 [Google Scholar]
  3. Guasch-Ferré, M., Bhupathiraju, S. N., & Hu, F. B. (2018). Use of metabolomics in improving assessment of dietary intake. Clinical Chemistry, 64(1), 8298. doi: 10.1373/clinchem.2017.272344 [Web of Science ®], [Google Scholar]
  4. Hyslop, D., & Imbens, G. (2001). Bias from classical and other forms of measurement error. Journal of Business & Economic Statistics, 19, 475481. doi: 10.1198/07350010152596727 [Taylor & Francis Online], [Google Scholar]
  5. Johnson, C. H., & Gonzalez, F. J. (2012). Challenges and opportunities of metabolomics. Journal of Cellular Physiology, 227(8), 29752981. doi: 10.1002/jcp.24002 [Google Scholar]
  6. Keogh, R. H., Strawbridge, A. D., & White, I. (2012). Correcting for bias due to misclassification when error-prone continuous exposures are misclassified. Epidemiologic Methods, 1(1), Article 9. [Google Scholar]
  7. Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., … Collins, G. S. (2015). Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Annals of Internal Medicine, 162(1), W173. doi: 10.7326/M14-0698 [Google Scholar]
  8. Prentice, R. L., & Huang, Y. (2018). Nutritional epidemiology methods and related statistical challenges and opportunities. Statistical Theory and Related Fields. Advance online publication. doi: 10.1080/24754269.2018.1466098 [Taylor & Francis Online], [Google Scholar]
  9. Tasevska, N., Midthune, D., Potischman, N., Subar, A. F., Cross, A. J., Bingham, S. A., … Kipnis, V. (2011). Use of the predictive sugars biomarker to evaluate self-reported total sugars intake in the observing protein and energy nutrition (OPEN) study. Cancer Epidemiology Biomarkers and Prevention, 20(3), 490500. doi: 10.1158/1055-9965.EPI-10-0820 [Google Scholar]