Analysing change in clinical trials using quasi-likelihoods
N. David Yanez,
Richard Kronmal,
Jennifer Nelson and
Todd Alonzo
Journal of Applied Statistics, 2002, vol. 29, issue 8, 1135-1145
Abstract:
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.
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0266476022000011210 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:29:y:2002:i:8:p:1135-1145
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/0266476022000011210
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().