Minimum MSE weights of adjusted summary
estimator of risk difference in multi-center studies
Minimum MSE weights of adjusted summary
estimator of risk difference in multi-center studies
The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practical use.
48-59
Viwatwongkasem, Chukiat
a81d7aeb-1120-4d25-92bd-07dd2315b0a8
Jitthavech, Jirawan
c7d3d146-f2fa-4c9a-8918-c5600b10af1d
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Lorchirachoonkul, Vichit
8afdf0b0-a0d8-4609-a949-30c49c14ec26
January 2012
Viwatwongkasem, Chukiat
a81d7aeb-1120-4d25-92bd-07dd2315b0a8
Jitthavech, Jirawan
c7d3d146-f2fa-4c9a-8918-c5600b10af1d
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Lorchirachoonkul, Vichit
8afdf0b0-a0d8-4609-a949-30c49c14ec26
Viwatwongkasem, Chukiat, Jitthavech, Jirawan, Böhning, Dankmar and Lorchirachoonkul, Vichit
(2012)
Minimum MSE weights of adjusted summary
estimator of risk difference in multi-center studies.
Open Journal of Statistics, 2 (1), .
(doi:10.4236/ojs.2012.21006).
Abstract
The simple adjusted estimator of risk difference in each center is easy constructed by adding a value c on the number of successes and on the number of failures in each arm of the proportion estimator. Assessing a treatment effect in multi-center studies, we propose minimum MSE (mean square error) weights of an adjusted summary estimate of risk difference under the assumption of a constant of common risk difference over all centers. To evaluate the performance of the proposed weights, we compare not only in terms of estimation based on bias, variance, and MSE with two other conventional weights, such as the Cochran-Mantel-Haenszel weights and the inverse variance (weighted least square) weights, but also we compare the potential tests based on the type I error probability and the power of test in a variety of situations. The results illustrate that the proposed weights in terms of point estimation and hypothesis testing perform well and should be recommended to use as an alternative choice. Finally, two applications are illustrated for the practical use.
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Published date: January 2012
Organisations:
Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 210577
URI: http://eprints.soton.ac.uk/id/eprint/210577
ISSN: 2161-718X
PURE UUID: 72bfb595-3966-4b9c-ad0d-219d1a050a3c
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Date deposited: 09 Feb 2012 16:57
Last modified: 15 Mar 2024 03:39
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Author:
Chukiat Viwatwongkasem
Author:
Jirawan Jitthavech
Author:
Vichit Lorchirachoonkul
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