If you need an accessible version of this item please contact JSTOR User Support

Parameter Orthogonality and Approximate Conditional Inference

D. R. Cox and N. Reid
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 49, No. 1 (1987), pp. 1-39
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2345476
Page Count: 39
  • Download PDF
  • Cite this Item

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support
Parameter Orthogonality and Approximate Conditional Inference
Preview not available

Abstract

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.

Page Thumbnails

  • Thumbnail: Page 
[1]
    [1]
  • Thumbnail: Page 
2
    2
  • Thumbnail: Page 
3
    3
  • Thumbnail: Page 
4
    4
  • Thumbnail: Page 
5
    5
  • Thumbnail: Page 
6
    6
  • Thumbnail: Page 
7
    7
  • Thumbnail: Page 
8
    8
  • Thumbnail: Page 
9
    9
  • Thumbnail: Page 
10
    10
  • Thumbnail: Page 
11
    11
  • Thumbnail: Page 
12
    12
  • Thumbnail: Page 
13
    13
  • Thumbnail: Page 
14
    14
  • Thumbnail: Page 
15
    15
  • Thumbnail: Page 
16
    16
  • Thumbnail: Page 
17
    17
  • Thumbnail: Page 
18
    18
  • Thumbnail: Page 
19
    19
  • Thumbnail: Page 
20
    20
  • Thumbnail: Page 
21
    21
  • Thumbnail: Page 
22
    22
  • Thumbnail: Page 
23
    23
  • Thumbnail: Page 
24
    24
  • Thumbnail: Page 
25
    25
  • Thumbnail: Page 
26
    26
  • Thumbnail: Page 
27
    27
  • Thumbnail: Page 
28
    28
  • Thumbnail: Page 
29
    29
  • Thumbnail: Page 
30
    30
  • Thumbnail: Page 
31
    31
  • Thumbnail: Page 
32
    32
  • Thumbnail: Page 
33
    33
  • Thumbnail: Page 
34
    34
  • Thumbnail: Page 
35
    35
  • Thumbnail: Page 
36
    36
  • Thumbnail: Page 
37
    37
  • Thumbnail: Page 
38
    38
  • Thumbnail: Page 
39
    39