2002
DOI: 10.1198/016214502760047005
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Corrected Score Estimation via Complex Variable Simulation Extrapolation

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Cited by 42 publications
(48 citation statements)
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“…In addition to regression calibration, simulation extrapolation (SIMEX) could be used to construct a less biased estimator for the regression coefficients [23]. Novick and Stefanski further applied SIMEX to the score function [24]. There are also some other methods that work well for some specific models.…”
Section: Discussionmentioning
confidence: 97%
“…In addition to regression calibration, simulation extrapolation (SIMEX) could be used to construct a less biased estimator for the regression coefficients [23]. Novick and Stefanski further applied SIMEX to the score function [24]. There are also some other methods that work well for some specific models.…”
Section: Discussionmentioning
confidence: 97%
“…Corrected scores, first proposed by Stefanski (1989) and Nakamura (1990), provide one approach to reducing bias incurred by covariate measurement error. Corrected scores have been defined in a variety of settings, including Poisson regression and failure time models (Nakamura, 1990;Augustin, 2004), and corrected scores constructed via simulation were proposed for a general class of regression models (Novick and Stefanski, 2002). A theoretical advantage of corrected scores is that they do not require assumptions on the distribution of the unobserved true covariates, and the resulting estimator converges to the limit of the true data estimator under misspecification of the regression model for the response (Carroll et al, 2006, p. 177).…”
Section: Introductionmentioning
confidence: 99%
“…2002). However, Novick and Stefanski (2002) show, through an example of logistic regression, that the method may be applied to some models for which (1.26) is not satisfied.…”
Section: E[^(y T X T 9)\y T X T ]=^(Y T X T 9)mentioning
confidence: 99%
“…A consistent estimator 0 can be obtained by solving the unbiased estimating equation (1.24). Novick and Stefanski (2002) show that \/n(0 -0) is asymptotically normally distributed and give the sandwich formula for the asymptotic variance. The complex variable extrapolation solves the problems of how to choose the extrapolation function and how to choose the A m 's.…”
Section: E[^(y T X T 9)\y T X T ]=^(Y T X T 9)mentioning
confidence: 99%
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