Variance Control Procedures

Heidi L. Weiss (), Jianrong Wu (), Katrina Epnere () and O. Dale Williams ()
Additional contact information
Heidi L. Weiss: Markey Cancer Center, University of Kentucky, Biostatistics and Bioinformatics Shared Resource Facility
Jianrong Wu: Markey Cancer Center, University of Kentucky, Biostatistics and Bioinformatics Shared Resource Facility
Katrina Epnere: WCG Statistics Collaborative
O. Dale Williams: University of North Carolina, Department of Biostatistics

Chapter 46 in Principles and Practice of Clinical Trials, 2022, pp 833-841 from Springer

Abstract: Abstract This chapter covers the concepts of variance and sources of variation for clinical trial data. Common metrics to quantify the extent of variability in relation to the mean are introduced as are clinical trial design techniques and statistical analysis methods to control and reduce this variation. The uses of variance as a data quality assessment tool in large-scale, long-term multicenter clinical trials are highlighted.

Keywords: Clinical trial; Variance; Systematic errors; Measurement errors; Random error; Coefficient of variation; Technical error; Matched design; Crossover design; Repeated measures design; Power; Sample size; Analysis of covariance; Multiple regression analysis; Data quality assessment (search for similar items in EconPapers)
Date: 2022
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:978-3-319-52636-2_218

Ordering information: This item can be ordered from
http://www.springer.com/9783319526362

DOI: 10.1007/978-3-319-52636-2_218

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 ().