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Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged.
Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu
Handbook of Measurement Error Models
Statistical Analysis with Measurement Error or Misclassification
Measurement Error in Nonlinear Models
Measurement Error and Misclassification in Statistics and Epidemiology
Radiation Risk Estimation
Measuring Agreement
Nonlinear Models for Repeated Measurement Data
Error and Inference
Measurement Uncertainties
Applied Biostatistical Principles and Concepts
Mixed Effects Models for Complex Data
Statistical Modeling and Applications