When using item response theory (IRT) models in educational and psychological measurement, it is standard practice to estimate the operating characteristics of test items from examinees' item responses alone. This is the final report of a project that employed Bayesian and empirical Bayesian methods to exploit additional information that is often available about test items (e.g., format, content, or cognitive processing requirements) or about examinees (e.g., educational background or demographic status). Although collateral information about examinees and items is rarely employed in IRT, it is straightforward to incorporate it using Bayesian and empirical Bayesian methods. Employing collateral information is mandatory to obtain correct Bayesian and empirical Bayesian inferences if it was used to assign items to examinees. Practical and theoretical results obtained in a series of six research reports are summarized. (Contains 3 tables and 12 references.) (Author/SLD)