Analysing change in clinical trials using quasi-likelihoods

N. David Yanez, Richard A. Kronmal, Jennifer C. Nelson, Todd A. Alonzo

Research output: Contribution to journalArticlepeer-review


In clinical trials, investigations focus upon whether a treatment affects a measured outcome. Data often collected include pre- and post-treatment measurements on each patient and an analysis of the change in the outcome is typically performed to determine treatment efficacy. Absolute change and relative change are frequently selected as the outcome. In selecting from these two measures, the analyst makes implicit assumptions regarding the mean and variance-mean relationship of the data. Some have provided ad hoc guidelines for selecting between the two measures. We present a more rigorous means of investigating change using quasi-likelihoods. We show that both absolute change and relative change are special cases of the specified quasi-likelihood model. A cystic fibrosis example is provided.

Original languageEnglish (US)
Pages (from-to)1135-1145
Number of pages11
JournalJournal of Applied Statistics
Issue number8
StatePublished - Nov 2002

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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