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Conditional estimation in two-stage adaptive designs
Stockholm University, Faculty of Social Sciences, Department of Statistics.
2017 (English)In: Biometrics, ISSN 0006-341X, E-ISSN 1541-0420Article in journal (Refereed) Epub ahead of print
Abstract [en]

We consider conditional estimation in two-stage sample size adjustable designs and the consequent bias. More specifically, we consider a design which permits raising the sample size when interim results look rather promising, and which retains the originally planned sample size when results look very promising. The estimation procedures reported comprise the unconditional maximum likelihood, the conditionally unbiased Rao-Blackwell estimator, the conditional median unbiased estimator, and the conditional maximum likelihood with and without bias correction. We compare these estimators based on analytical results and a simulation study. We show how they can be applied in a real clinical trial setting.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Adaptive design, Conditional estimation, Sample size recalculation, Two-stage design
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:su:diva-136195DOI: 10.1111/biom.12642OAI: oai:DiVA.org:su-136195DiVA: diva2:1051028
Available from: 2016-11-30 Created: 2016-11-30 Last updated: 2017-01-23

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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