A new classification approach for comparing two active treatments when there is no prior projection on which one is better

Stat Med. 2011 Dec 30;30(30):3488-95. doi: 10.1002/sim.4402. Epub 2011 Nov 15.

Abstract

We developed a new classification approach in this paper to compare two active treatments. This approach is especially useful when there is no prior judgment on which treatment is better and the traditional hypothesis testing approach is thus not applicable. Our method classifies all the possible outcomes into categories and draws conclusions on the difference in the outcome measurement between two treatment arms according to the location of the confidence interval for the treatment difference in the response variable. This method controls the misclassification rate regardless of the true difference in the response between the two treatment arms. The method was applied to a diabetes clinical trial.

Publication types

  • Comparative Study

MeSH terms

  • Algorithms
  • Biostatistics
  • Confidence Intervals
  • Diabetes Mellitus / blood
  • Diabetes Mellitus / drug therapy
  • Glycated Hemoglobin / metabolism
  • Humans
  • Insulin Lispro / administration & dosage
  • Outcome Assessment, Health Care / statistics & numerical data
  • Randomized Controlled Trials as Topic / classification
  • Randomized Controlled Trials as Topic / statistics & numerical data*
  • Therapeutics / classification
  • Treatment Outcome

Substances

  • Glycated Hemoglobin A
  • Insulin Lispro
  • hemoglobin A1c protein, human