The number of longitudinal data archives is growing almost daily, yet no resource exists to help understand the relationship between research questions and archival data--until now. Drawing on a single project, the Lewis Terman Study at Stanford University, the authors illustrate how to use the model-fitting process to select and fit the right data set to a particular research problem. Employing a step-by-step approach, this handy volume covers the measurement of historical influences, the adaptation of existing coding schemes to temporal patterns that are characteristic of life records, and the recasting of archival materials to illuminate contemporary questions that the data were not designed to answer.
Although the growth of longitudinal data archives is one of the most dramatic developments in the behavioural sciences, there has been a barrier to the effective use of these files due to a lack of understanding of the relation between research questions and archival data - until now. The authors of this volume illustrate how to use the model-fitting process to select and fit the right data set to a particular research problem. Beginning with an introduction to the general issues in working with archival data, the book takes the reader through steps in the recasting of data and question, using substantive examples from the life course, such as temporal patterns of physical and emotional health as well as pathways to retirement.
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