A0351
Title: Modeling measurement error in official crime data
Authors: Matthew Koslovsky - Colorado State University (United States) [presenting]
Abstract: Measurement error in multinomial data is a well-known and well-studied inferential problem that is encountered in many fields, including engineering, biomedical and omics research, ecology, finance, official statistics, and social sciences. Methods developed to accommodate measurement error in multinomial data are typically equipped to handle false negatives or false positives, but not both. A unified framework is provided for accommodating both forms of measurement error using a Bayesian hierarchical approach. The proposed method's performance is demonstrated on simulated data, and it is applied to official crime data.
