 Completeness and unbiased estimation of mean vector in the multivariate group sequential caseAiyi Liu, Chengqing Wu, Kai F. Yu and Weishi Yuan Journal of Multivariate Analysis, 2007, vol. 98, issue 3, 505-516 Abstract: We consider estimation after a group sequential test about a multivariate normal mean, such as a [chi]2 test or a sequential version of the Bonferroni procedure. We derive the density function of the sufficient statistics and show that the sample mean remains to be the maximum likelihood estimator but is no longer unbiased. We propose an alternative Rao-Blackwell type unbiased estimator. We show that the family of distributions of the sufficient statistic is not complete, and there exist infinitely many unbiased estimators of the mean vector and none has uniformly minimum variance. However, when restricted to truncation-adaptable statistics, completeness holds and the Rao-Blackwell estimator has uniformly minimum variance. Keywords: Bias; Interim; analysis; Mean; squared; error; Medical; trials; Minimum; variance; Multiple; endpoints; Restricted; completeness; Truncation-adaptation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:98:y:2007:i:3:p:505-516 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Multivariate Analysis is currently edited by de Leeuw, J. More articles in Journal of Multivariate Analysis from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.