Abstract
Quasi-score equations derived from corrected mean and variance functions allow for consistent parameter estimation under measurement error. However, the practical use of some approaches relying on this general methodo\-logical principle was strongly limited by the assumptions underlying them: only one covariate was allowed to be measured with non-negligible error, and, additionally, this covariate had to be conditionally independent of the other covariates. This paper extends basic principles of this method to multivariate and flexible models in a way that, on the one hand, retains the neat statistical properties, but on the other hand, manages to do without the restrictive assumptions needed up to now.
Item Type: | Paper |
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Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1586-9 |
Language: | English |
Item ID: | 1586 |
Date Deposited: | 05. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |