Data Quality in Longitudinal Research

This book provides an overview of the central issues of data quality in longitudinal research, with a focus on data relevant for studying individual development. Topics covered include reliability, validity, sampling, aggregation, and the correspondence between theory and method; more specific, practical issues in longitudinal research, such as the drop-out problem and issues of confidentiality are also addressed. The volume is the result of an interdisciplinary endeavour by leading European scientists to discuss appropriate ways of handling various types of longitudinal data, including psychiatric data, alcohol data, and criminal data.