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Conditional estimation in two-stage adaptive designs

Broberg, Per LU and Miller, Frank (2017) In Biometrics 73(3). p.895-904
Abstract

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.

Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Adaptive design, Conditional estimation, Sample size recalculation, Two-stage design
in
Biometrics
volume
73
issue
3
pages
895 - 904
publisher
INTERNATIONAL BIOMETRIC SOC,
external identifiers
  • scopus:85010190061
  • pmid:28099993
  • wos:000411878000021
ISSN
0006-341X
DOI
10.1111/biom.12642
language
English
LU publication?
yes
id
40ccbeb3-0def-4e4f-94de-0b165c1dc302
date added to LUP
2017-02-01 15:21:38
date last changed
2025-01-12 20:34:44
@article{40ccbeb3-0def-4e4f-94de-0b165c1dc302,
  abstract     = {{<p>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.</p>}},
  author       = {{Broberg, Per and Miller, Frank}},
  issn         = {{0006-341X}},
  keywords     = {{Adaptive design; Conditional estimation; Sample size recalculation; Two-stage design}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{895--904}},
  publisher    = {{INTERNATIONAL BIOMETRIC SOC,}},
  series       = {{Biometrics}},
  title        = {{Conditional estimation in two-stage adaptive designs}},
  url          = {{http://dx.doi.org/10.1111/biom.12642}},
  doi          = {{10.1111/biom.12642}},
  volume       = {{73}},
  year         = {{2017}},
}