Data Quality in Longitudinal Research

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Data Quality in Longitudinal Research

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  • 製本 Hardcover:ハードカバー版
  • 言語 ENG
  • 商品コード 9780521380911
  • DDC分類 610.72

Full Description


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.

Table of Contents

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.