Using the entire cohort in the receiver operating characteristic analysis maximizes precision of the minimal important difference

J Clin Epidemiol. 2009 Apr;62(4):374-9. doi: 10.1016/j.jclinepi.2008.07.009. Epub 2008 Nov 14.


Objective: We compared the minimal important difference (MID) values obtained by the receiver operating characteristics (ROC) curve approach using different strategies on four outcome measures to guide the optimal use of ROC curve.

Study design and setting: Studies of two psychometric scales (Rhinoconjunctivitis Quality-of-Life Questionnaire [RQLQ] and Chronic Respiratory Questionnaire [CRQ]) and two clinimetric indices (Pediatric Ulcerative Colitis Activity Index [PUCAI] and Pediatric Crohn's Disease Activity Index [PCDAI]) instruments provided prospective longitudinal data. The MID was calculated from 7- and 15-point global ratings of change dichotomized in multiple ways, using the ROC curve method. Analysis was performed twice: first, using only the two groups adjacent to the dichotomization point (e.g., including only patients who had a small vs. moderate change); and second, using the entire cohort split at the same cutoff (e.g., including both unchanged subjects with those with small change vs. those who experienced moderate or large change combined).

Results: Using the entire cohort, rather than just those with ratings adjacent to the dichotomization point, yielded more precise and sensible MID estimates. With one exception, high precision was obtained when using the ROC curve method for any cutoff on the rating scale.

Conclusion: When calculating the MID using the ROC curve method, the use of the entire cohort maximizes precision.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cohort Studies*
  • Prognosis
  • ROC Curve*
  • Sensitivity and Specificity
  • Severity of Illness Index*
  • Surveys and Questionnaires / standards*