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Variable selection and transformation in linear regression models
- Authors
- Yeo, IK
- Issue Date
- May-2005
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- bootstrap calibration; cox statistic; Kullback-Leibler information; Monte Carlo estimation; parametric transformation
- Citation
- STATISTICS & PROBABILITY LETTERS, v.72, no.3, pp 219 - 226
- Pages
- 8
- Journal Title
- STATISTICS & PROBABILITY LETTERS
- Volume
- 72
- Number
- 3
- Start Page
- 219
- End Page
- 226
- ISSN
- 0167-7152
1879-2103
- Abstract
- We develop a method for comparing separate linear models, for a common response variable that may be expressed on different scales and may be described by distinct explanatory variables. A method of stochastic simulation is used to approximate the fitted maximum likelihood estimates and then the Cox statistic is computed to test separate linear models. The bootstrap iteration is also used to calibrate confidence intervals to correct the test level. (c) 2005 Elsevier B.V. All rights reserved.
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