This book is a practical guide for the analysis of longitudinal behavioural data. Longitudinal data consist of repeated measures collected on the same subjects over time.

This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at www.psypress.com/longitudinal-data-analysis. Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes. The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis. An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.

The Committee and the Board on Children, Youth, and Families convened in September a workshop to discuss ways to foster greater collaboration and sharing of information among principal investigators of several longitudinal surveys of children. Among many topics discussed were issues of coverage and balance of content, sampling design and weighting, measurement and analysis, field operations, legitimation and retention of cases, data disclosure and dissemination, and resources available for longitudinal studies. The workshop was sponsored by the National Institute on Justice.

This 2006 book is based on two longitudinal studies of behavior development, both conducted in Finland, a living laboratory setting for longitudinal research. Much of the book reports results from a longitudinal study begun in Jyväskylä, Finland, in 1968, when its participants were school children. This longitudinal study is complemented by two Finnish twin-family studies, with parallel measures and overlapping aims, to yield insights into genetic and environmental sources of variation in early development and later outcomes. An array of findings from the two sets of longitudinal studies are presented, set within a theoretical framework of socioemotional development, and focused on both individual and familial predictors of health-related outcomes from childhood to early adulthood. Many contributors to this edited volume represent a second-tier of Finnish-USA collaborators. They analyzed data from the longitudinal studies as part of their advanced training, and their contributions to the book report results of such analyses.

This volume is the product of a course on longitudinal prospective re search arranged by the three editors in Arhus, Denmark, in 1978. The course was supported by the Nordisk Kulturfond for young researchers from the Nordic countries, who had planned or had simply involved themselves in longitudinal prospective research projects of various kinds. The twenty-six participants represented a wide range of professions: statisticians, psychologists, psychiatrists, nutritionists, and public health researchers. The teachers came from many countries and represented many disciplines. The course was very successful, especially from the point of view of the quality and investment of the teachers. We felt also that the course met a strong need in this relatively new field of research. Therefore, we asked the teachers to prepare written versions of their lectures so that they could have wider dissemination; they agreed to do so. The present book is composed of these contributions. The first chap ter, after outlining some of the problems with traditional strategies in mental health research, goes on to suggest some of the possible preven tive applications of longitudinal research methods. Included in Parts II and III are papers on design problems and on the tools of long-term research, such as genetics and classification, biological measurements, epidemiological guidelines, statistical models, disease registers, and de velopmental psychology.

Longitudinal data analysis for biomedical and behavioral sciences This innovative book sets forth and describes methods for the analysis of longitudinaldata, emphasizing applications to problems in the biomedical and behavioral sciences. Reflecting the growing importance and use of longitudinal data across many areas of research, the text is designed to help users of statistics better analyze and understand this type of data. Much of the material from the book grew out of a course taught by Dr. Hedeker on longitudinal data analysis. The material is, therefore, thoroughly classroom tested and includes a number of features designed to help readers better understand and apply the material. Statistical procedures featured within the text include: * Repeated measures analysis of variance * Multivariate analysis of variance for repeated measures * Random-effects regression models (RRM) * Covariance-pattern models * Generalized-estimating equations (GEE) models * Generalizations of RRM and GEE for categorical outcomes Practical in their approach, the authors emphasize the applications of the methods, using real-world examples for illustration. Some syntax examples are provided, although the authors do not generally focus on software in this book. Several datasets and computer syntax examples are posted on this title's companion Web site. The authors intend to keep the syntax examples current as new versions of the software programs emerge. This text is designed for both undergraduate and graduate courses in longitudinal data analysis. Instructors can take advantage of overheads and additional course materials available online for adopters. Applied statisticians in biomedicine and the social sciences can also use the book as a convenient reference.