U is for unease: Reasons for mistrusting overlap measures for reporting clinical trials

Stephen Senn*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)

Abstract

In recent years a number of authors have promoted approaches to measuring the results of clinical trials that depend on the degree of overlap between the distribution of results from the treatment and the control group. In their enthusiasm for such measures, however, many have overlooked a particular problem, namely that while they seem to overcome a certain arbitrary element in measuring the shift between groups in a given trial, they still depend very strongly on the distribution of the results from trial to trial.

Original languageEnglish
Pages (from-to)302-309
Number of pages8
JournalStatistics in Biopharmaceutical Research
Volume3
Issue number2
DOIs
Publication statusPublished - 2011
Externally publishedYes

Keywords

  • Cohen's d
  • Effect size
  • Mann-Whitney
  • Proportion of similar responses
  • Sigma divided measure

Fingerprint

Dive into the research topics of 'U is for unease: Reasons for mistrusting overlap measures for reporting clinical trials'. Together they form a unique fingerprint.

Cite this