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.

Preface; List of contributors; 1. General issues about data quality in longitudinal research L. Bergman and D. Magnusson; 2. Improving the quality of psychiatric data: classification, cause and course M. Rutter and A. Pickles; 3. Data in epidemiological longitudinal research G. Eklund; 4. Data in pediatric longitudinal research R. Zetterstrom; 5. Alcohol data in longitudinal research A. Uchtenhagen; 6. Retrospective data, undesirable behaviour, and the longitudinal perspective C.-G. Janson; 7. Minimising attrition in longitudinal research: methods in tracing and securing cooperation in a 24-year follow-up study D. P. Farrington, B. Gallagher, L. Morley, R. J. St Ledger and D. J. West; 8. Minimising attrition in longitudinal studies: means or end? M. Murphy; 9. N's, times and number of variables in longitudinal research G. Rudinger and P. K. Wood; 10. Stability of patterns and patterns of stability in personality development J. B. Asendorpf and F. E. Weinert; 11. Beyond correlations: from group data analyses to single case studies F. Schulsinger; 12. Age, period, and cohort in the study of the life course: a comparison of classical A-P-C-analysis with event history analysis or farewell to lexis? K. U. Mayer and J. Huinink; 13. New possibilities for longitudinal studies of intergenerational factors in child health and development J. Fox and K. Fogelman; 14. Archiving longitudinal data A. Colby and E. Phelps.