Author: F. Schulsinger
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Genre: Social Science
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.
This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website (www.intensivelongitudinal.com).
Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: descriptive methods for delineating trends over time linear mixed regression models with both fixed and random effects covariance pattern models on correlated errors generalized estimating equations nonlinear regression models for categorical repeated measurements techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.
This new volume reviews longitudinal models and analysis procedures for use in the behavioral and social sciences. Written by distinguished experts in the field, the book presents the most current approaches and theories, and the technical problems that may be encountered along the way. Readers will find new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the research design and the data available. Divided into two parts, Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network analysis and/or growth-curve data. The focus of part two is on the application of longitudinal modeling in a variety of disciplines. The book features applications such as heterogeneity on the patterns of a firm's profit, on house prices, and on delinquent behavior: non-linearity in growth in assessing cognitive aging; measurement error issues in longitudinal research; and distance association for the analysis of change. Part two clearly demonstrates the caution that should be taken when applying longitudinal modeling as well as in the interpretation of the results. Longitudinal Models in the Behavioral and Related Sciences is ideal for advanced students and researchers in psychology, sociology, education, economics, management, medicine, and neuroscience.
Author: Enid E. Haag
Publisher: Greenwood Publishing Group
Release Date: 1988
This unique research tool will lead researchers and practitioners to published materials and documents that can provide answers needed for making informed decisions regarding issues related to today's children. Comprised of approximately 1,400 entries, this guide reflects an interdisciplinary approach citing sources from the fields of psychology, education, sociology, medicine, law, home economics, and the arts. Chapter 12, with its focus on creativity, is unique in its coverage of drama, dance, art, and music. The bibliography of music resources by Marian Ritter is the first of its kind. Appropriate for a wide range of users, this book is designed for students just beginning to seek answers to questions concerning children, as well as professionals with years of experience in dealing with childhood problems. It will also be helpful for those wishing to learn about using databases in the literature searching process. A carefully organized table of contents and complete subject index allow for ease of entry location.
Author: Alexander von Eye
Publisher: Psychology Press
Release Date: 2014-04-04
A comprehensive resource for analyzing a variety of categorical data, this book emphasizes the application of many recent advances of longitudinal categorical statistical methods. Each chapter provides basic methodology, helpful applications, examples using data from all fields of the social sciences, computer tutorials, and exercises. Written for social scientists and students, no advanced mathematical training is required. Step-by-step command files are given for both the CDAS and the SPSS software programs.
Author: Jeffrey D. Long
Release Date: 2011-10-31
Genre: Social Science
This book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.
Author: David Magnusson
Publisher: Cambridge University Press
Release Date: 2006-12-14
Longitudinal research is an essential element in the investigation of human development over time, with considerable advantages over more widely used cross-sectional research designs. This book examines the scope for longitudinal studies in a range of developmental fields, emphasizing the advantages of this approach for the investigation of causal mechanisms and processes and the dynamics of development over the life-span. It also discusses methodological issues and some of the practical and ethical problems that longitudinal research may present. Contributors review normal and disordered development in the emotional, cognitive and social domains, including valuable discussions of gene-environment interactions, the maturation of the human brain and issues relating to aging.
Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. Written for non-mathematically-oriented readers, this text features: A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data An emphasis on how the terminology, interpretation, and estimation of familiar general linear models relates to those of more complex models for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers’ understanding of the overall model-building process Sample results sections for each example to provide useful templates for published reports Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and Mplus at www.PilesOfVariance.com to help readers apply the models to their own data The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data. Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.
Author: Scott M. Hofer
Release Date: 2008-03-20
"Provides a unique perspective. I am particularly impressed with the sections on innovative design and methods to investigate cognitive aging and the integrative perspectives. None of the existing texts covers this material to the same level." —Donna J. La Voie, Saint Louis University "The emphasis on integrating the literature with theoretical and methodological innovations could have a far-reaching impact on the field." —Deb McGinnis, Oakland University The Handbook of Cognitive Aging: Interdisciplinary Perspectives clarifies the differences in patterns and processes of cognitive aging. Along with a comprehensive review of current research, editors Scott M. Hofer and Duane F. Alwin provide a solid foundation for building a multidisciplinary agenda that will stimulate further rigorous research into these complex factors. Key Features Gathers the widest possible range of perspectives by including cognitive aging experts in various disciplines while maintaining a degree of unity across chapters Examines the limitations of the extant literature, particularly in research design and measurement, and offers new suggestions to guide future research Highlights the broad scope of the field with topics ranging from demography to development to neuroscience, offering the most complete coverage available on cognitive aging
Author: Committee on National Statistics
Publisher: National Academies Press
Release Date: 1998-09-23
Genre: Social Science
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.