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JSRI 2019, 16(1): 255-286 Back to browse issues page
Likelihood Inference in the Random Effects Logistic Regression Model with ‎Response Misclassification and Covariate Subject to Measurement Error‎
Maryam Ahangari, Mousa Golalizadeh *1, Zahra Rezaei Ghahroodi
1- , golalizadeh@modares.ac.ir
Abstract:   (32 Views)
‎Generalized linear mixed models (GLMMs) are common methods for the analysis of clustered data‎. ‎In many longitudinal and hierarchical epidemiological frameworks‎, ‎accurate measurements of variables are invalid or expensive to be obtained and there might be situations that both the response and covariate variables are likely to be mismeasured‎. ‎Insensitivity of errors in either covariate or response variable is‎, ‎not always plausible‎. ‎With nonlinear regression models for the outcome process‎, ‎classification errors for binary responses and measurement error in covariates basically needs to be accounted for in order to make conclusive inferences‎. ‎In this article‎, ‎we provide an approach to simultaneously adjust for non-differential misclassification in the correlated binary response and classical measurement error in the covariates‎, ‎using the multivariate Gauss-Hermite quadrature technique for the approximation of the likelihood function‎. ‎Simulation studies are then conducted to inform the effects of correcting for measurement error and misclassification on the estimation of regression parameters‎. ‎The application of the multivariate Gauss-Hermite quadrature method in the conjunction of measurement error and misclassification problems is further highlighted with real-world data based on a multilevel study of contraceptive methods used by women in Bangladesh‎.
Keywords: Measurement Error, Binary Response, Multivariate Gauss-Hermite Quadrature, Random Effects Logistic Regression Model, Misclassification.‎
Full-Text [PDF 594 kb]   (10 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/11/26 | Accepted: 2021/01/31 | Published: 2019/09/19
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Ahangari M, golalizadeh M, Rezaei Ghahroodi Z. Likelihood Inference in the Random Effects Logistic Regression Model with ‎Response Misclassification and Covariate Subject to Measurement Error‎. JSRI. 2019; 16 (1) :255-286
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Volume 16, Issue 1 (9-2019) Back to browse issues page
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