 | Measurement Error: Models, Methods, and Applications Subjects: Bioscience; Mathematics & Statistics; Epidemiology; Biology; Statistics & Probability; Statistics for the Biological Sciences; Statistics; 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 John P. Buonaccorsi is a professor in the Department of Mathematics and Statistics at the University of Massachusetts, Amherst. |
