Handbook of Measurement Error Models
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portes grátis
Handbook of Measurement Error Models
Gustafson, Paul; Delaigle, Aurore; Yi, Grace Y.
Taylor & Francis Ltd
10/2021
578
Dura
Inglês
9781138106406
15 a 20 dias
993
Descrição não disponível.
1. Measurement Error models - A brief account of past developments and modern advancements. 2. The impact of unacknowledged measurement error. 3. Identifiability in measurement error. 4. Partial learning of misclassification parameters. 5. Using instrumental variables to estimate models with mismeasured regressors. 6. Likelihood Methods for Measurement Error and Misclassification. 7. Regression calibration for covariate measurement error. 8. Conditional and corrected score methods. 9. Semiparametric methods for measurement error and misclassification. 10. Deconvolution kernel density estimation. 11. Nonparametric deconvolution by Fourier transformation and other related approaches. 12. Deconvolution with unknown error distribution. 13. Nonparametric inference methods for Berkson errors. 14. Nonparametric Measurement Errors Models for Regression. 15. Covariate measurement error in survival data. 16. Mixed effects models with measurement errors in time-dependent covariates. 17. Estimation in mixed-effects models with measurement error. 18. Measurement error in dynamic models . 19. Spatial exposure measurement error in environmental epidemiology. 20. Measurement error as a missing data problem. 21. Measurement error in causal inference. 23. Bayesian adjustment for misclassification. 24. Bayesian approaches for handling covariate measurement error
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Measurement Error Model;nonparametric inference;Measurement Error Effects;regression analysis with measurement error;Regression Calibration;Covariate Measurement Error;Measurement Errors;Identifiability;Regression Models;Error Prone Covariates;Bayesian adjustment;Classical Measurement Error;Application with error-prone data;Conditional Score;Deconvolution Kernel;Measurement Error Correction;Generalized Linear Mixed Models;Berkson I;Conditional Expectation;Naive Estimator;Time Dependent Covariates;Measurement Error Variance;Exposure Measurement Error;Error Free Covariates;NLME Model;Conditional Moments;Deconvolution Problems;LME Model;Error Density;Linear Measurement Error Model
1. Measurement Error models - A brief account of past developments and modern advancements. 2. The impact of unacknowledged measurement error. 3. Identifiability in measurement error. 4. Partial learning of misclassification parameters. 5. Using instrumental variables to estimate models with mismeasured regressors. 6. Likelihood Methods for Measurement Error and Misclassification. 7. Regression calibration for covariate measurement error. 8. Conditional and corrected score methods. 9. Semiparametric methods for measurement error and misclassification. 10. Deconvolution kernel density estimation. 11. Nonparametric deconvolution by Fourier transformation and other related approaches. 12. Deconvolution with unknown error distribution. 13. Nonparametric inference methods for Berkson errors. 14. Nonparametric Measurement Errors Models for Regression. 15. Covariate measurement error in survival data. 16. Mixed effects models with measurement errors in time-dependent covariates. 17. Estimation in mixed-effects models with measurement error. 18. Measurement error in dynamic models . 19. Spatial exposure measurement error in environmental epidemiology. 20. Measurement error as a missing data problem. 21. Measurement error in causal inference. 23. Bayesian adjustment for misclassification. 24. Bayesian approaches for handling covariate measurement error
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Measurement Error Model;nonparametric inference;Measurement Error Effects;regression analysis with measurement error;Regression Calibration;Covariate Measurement Error;Measurement Errors;Identifiability;Regression Models;Error Prone Covariates;Bayesian adjustment;Classical Measurement Error;Application with error-prone data;Conditional Score;Deconvolution Kernel;Measurement Error Correction;Generalized Linear Mixed Models;Berkson I;Conditional Expectation;Naive Estimator;Time Dependent Covariates;Measurement Error Variance;Exposure Measurement Error;Error Free Covariates;NLME Model;Conditional Moments;Deconvolution Problems;LME Model;Error Density;Linear Measurement Error Model
