Multiple Statistical Inferences
Ton J. Cleophas,
Aeilko H. Zwinderman and
Toine F. Cleophas
Additional contact information
Ton J. Cleophas: European Interuniversity College of Pharmaceutical Medicine Lyon
Aeilko H. Zwinderman: European Interuniversity College of Pharmaceutical Medicine Lyon
Toine F. Cleophas: Technical University
Chapter Chapter 7 in Statistics Applied to Clinical Trials, 2002, pp 73-82 from Springer
Abstract:
Abstract Clinical trials often compare the efficacy of several new treatments and often use many efficacy variables. Also, after overall testing for significant differences, additional questions about subgroups differences or about what variables do or do not contribute to the efficacy results. Assessment of such questions introduces the statistical problem of multiple comparison and multiple testing, which increases the risk of false positive statistical results, and thus increases the type-I error risk. In this chapter simple methods are discussed which can help to control this risk.
Keywords: Composite Variable; Primary Variable; Honestly Significant Difference; Nominal Level; Efficacy Variable (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:sprchp:978-94-010-0337-7_7
Ordering information: This item can be ordered from
http://www.springer.com/9789401003377
DOI: 10.1007/978-94-010-0337-7_7
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().