David Magnusson / R. Bergman (eds.)

Data Quality in Longitudinal Research

Herausgeber: Magnusson, David; Bergman, Lars R.

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 298
• Erscheinungstermin: 27. März 2015
• Englisch
• Abmessung: 235mm x 157mm x 21mm
• Gewicht: 585g
• ISBN-13: 9780521380911
• ISBN-10: 052138091X
• Artikelnr.: 26676877

Inhaltsangabe

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.