Skrondal, Anders and Kuha, Jouni 
ORCID: 0000-0002-1156-8465
(2012)
Improved regression calibration.
Psychometrika, 77 (4).
pp. 649-669.
ISSN 0033-3123
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Abstract
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration approach, a general pseudo maximum likelihood estimation method based on a conveniently decomposed form of the likelihood. It is both consistent and computationally efficient, and produces point estimates and estimated standard errors which are practically identical to those obtained by maximum likelihood. Simulations suggest that improved regression calibration which is easy to implement in standard software, works well in a range of situations.
| Item Type: | Article |
|---|---|
| Official URL: | http://www.psychometrika.org/journal/Psychometrika... |
| Additional Information: | © 2012 The Psychometric Society |
| Divisions: | Methodology Statistics |
| Subjects: | H Social Sciences > HA Statistics |
| Date Deposited: | 29 May 2012 10:20 |
| Last Modified: | 12 Dec 2024 00:08 |
| URI: | http://eprints.lse.ac.uk/id/eprint/44135 |
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