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Cited by 1,366

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Parameter Orthogonality and Approximate Conditional Inference

Cox, D. R., Reid, N.·1987·Journal of the Royal Statistical Society Series B: Statistical Methodology

Abstract

SUMMARY: We consider inference for a scalar parameter Ψ in the presence of one or more nuisance parameters. The nuisance parameters are required to be orthogonal to the parameter of interest, and the construction and interpretation of orthogonalized parameters is discussed in some detail. For purposes of inference we propose a likelihood ratio statistic constructed from the conditional distribution of the observations, given maximum likelihood estimates for the nuisance parameters. We consider to what extent this is preferable to the profile likelihood ratio statistic in which the likelihood function is maximized over the nuisance parameters. There are close connections to the modified profile likelihood of Barndorff-Nielsen (1983). The normal transformation model of Box and Cox (1964) is discussed as an illustration.

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Crossref · 10.1111/j.2517-6161.1987.tb01422.x

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Metadata

Authors
Cox, D. R., & Reid, N.
Venue
Journal of the Royal Statistical Society Series B: Statistical Methodology
Published
1987-09-01
Volume
49
Issue
1
Pages
1-18
ISSN
  • 1369-7412 (ISSN-L)
  • 1467-9868
OpenAlex
W1959492
Cited by
1,366
References
3
FWCI
29.81
Type
journal article
Language
en
Open access
closed

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