Bias of estimates of secondary parameters in linear-boundary sequential tests

Vladimir Dragalin, Benjamin Yakir, W. J. Hall

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The context is that of a sequential trial based on Brownian motion with
linear stopping boundaries, possibly truncated. Along with the monitoring
process, a secondary Gaussian process with constant mean is observed; the
mean is to be estimated once the monitoring process reaches a boundary.
We provide a formula for the conditional bias, conditioning on the final
position of the monitoring process; this formula can then be integrated
to obtain an overall bias. Special attention is given to evaluating bias -
mathematically and by Monte Carlo - of the Kaplan-Meier estimator of
one of the survival functions (and similarly for the Nelson-Aalen estimator of the corresponding cumulative hazard function) upon completion of
a survival-analysis-based.
Original languageAmerican English
Title of host publicationInstitute of Mathematical Statistics Lecture Notes - Monograph Series
Editors John E. Kolassa , David Oakes
PublisherInstitute of Mathematical Statistics
Pages13-28
Number of pages16
ISBN (Print)0749-2170
DOIs
StatePublished - 2003

Publication series

NameInstitute of Mathematical Statistics Lecture Notes - Monograph Series
Volume43

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