Different methods to analyze clinical experiments with multiple endpoints: A comparison on real data

M. Comelli, C. Klersy

Research output: Contribution to journalArticle


In many clinical experiments multiple measurements are required for evaluation of the results. Several methods have been illustrated in the literature to deal with this problem. Some of these solve the problem of multiple testing bias just by looking at the significance of the most pronounced difference. On the other band, some other methods are designed to take into account all the information available from an experiment. The purpose of this paper is to review these methods and compare the results they gave when applied to a Clinical trial in Which drug efficacy was assessed by 14 outcome measures.

Original languageEnglish
Pages (from-to)115-125
Number of pages11
JournalJournal of Biopharmaceutical Statistics
Issue number2
Publication statusPublished - 1996



  • Adjusted p-values
  • bonferroni correction
  • Multiple endpoints
  • Rank-based analysis

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Pharmacology, Toxicology and Pharmaceutics(all)

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