Measurement Error in Nonlinear Models: a Modern Perspective

By A. Roddam. 2008

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Forest Growth and Yield Modeling (2011, methodology): “Correction methods are numerous and covered for linear and nonlinear models in Fuller (1987) and Carroll et al. (2006), respectively.”
Bayesian analysis of measurement error models using integrated nested Laplace approximations (2015, methodology): “Carroll et al. (2006) used an ME model fitted via a maximum likelihood method and a Bayesian approach using MCMC sampling, denoted here as methods C.ML and C.MCMC.”
Correcting for Test Score Measurement Error in ANCOVA Models for Estimating Treatment Effects (2014, methodology): “Also known as ‘‘errors in variables’’ regression (Carroll et al., 2006; Fuller, 2006), this approach corrects elements of the cross-product matrix in the regression of Y on ðT ;Z; ŷÞ to produce consistent estimates of the parameters of Model 3.”
A ug 2 01 4 Local Privacy , Data Processing Inequalities , and Minimax Rates (2018, background): “3 Error-in-variables models As a final remark on related work, we touch briefly on errors-in-variables models [14, 31], which have been the subject of extensive study.”
Modeling errors in daily precipitation measurements: Additive or multiplicative? (2013, methodology): “There are also theoretical treatments to the modeling of errors in both the measurements and the reference data (errors-in-variables theories) [e.g., Carroll et al., 2006], which are beyond the scope of the current study.”