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OBJECTIVE BAYESIAN INFERENCE FOR RATIOS OF REGRESSION COEFFICIENTS IN LINEAR MODELS

The paper considers the standard linear multiple regression model where the parameter of interest is a ratio of two regression coefficients. The general model includes the calibration model, the Fieller-Creasy problem, slope-ratio assays, parallel-line assays and bioequivalence. We provide a... Full description

1st Person: Ghosh, Malay
Additional Persons: Yin, Ming verfasserin; Kim, Yeong-Hwa verfasserin
Source: in Statistica Sinica Vol. 13, No. 2 (2003), p. 409-422
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Type of Publication: Article
Language: English
Published: 2003
Keywords: research-article
Online: Volltext
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Summary: The paper considers the standard linear multiple regression model where the parameter of interest is a ratio of two regression coefficients. The general model includes the calibration model, the Fieller-Creasy problem, slope-ratio assays, parallel-line assays and bioequivalence. We provide a unified objective Bayesian analysis for such problems. Both reference priors and probability matching priors are found. Based on some numerical findings, our recommended prior is the one-at-a-time reference prior. The analysis is greatly facilitated by an orthogonal (Cox and Reid (1987)) reparameterization of the original parameter vector.
Item Description: Copyright: © 2003 Statistica Sinica
Physical Description: Online-Ressource
ISSN: 1996-8507

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