Maximum Likelihood Estimation of Generalized Linear Models with Covariate Measurement Error

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Maximum likelihood estimation of generalized linear models with covariate measurement error

Generalized linear models with covariate measurement error can be estimated by maximum likelihood using gllamm, a program that fits a large class of multilevel latent variable models (Rabe-Hesketh, Skrondal, and Pickles 2004b). The program uses adaptive quadrature to evaluate the log-likelihood, producing more reliable results than many other methods (Rabe-Hesketh, Skrondal, and Pickles 2002). ...

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ژورنال

عنوان ژورنال: The Stata Journal: Promoting communications on statistics and Stata

سال: 2003

ISSN: 1536-867X,1536-8734

DOI: 10.1177/1536867x0400300408