Conditional estimation in two-stage adaptive designs
(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:
https://lup.lub.lu.se/record/40ccbeb3-0def-4e4f-94de-0b165c1dc302
- author
- Broberg, Per LU and Miller, Frank
- organization
- publishing date
- 2017
- 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
- 2024-09-07 07:22:59
@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}},
}