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.
Highlighting the progress made by researchers in using Web-based surveys for data collection, this timely volume summarizes the experiences of leading behavioral and social scientists from Europe and the US who collected data using the Internet. Some chapters present theory, methodology, design, and implementation, while others focus on best practice examples and/or issues such as data quality and understanding paradata. A number of contributors applied innovative Web-based research methods to the LISS panel of CentERdata collected from over 5,000 Dutch households. Their findings are presented in the book. Some of the data is available on the book website. The book addresses practical issues such as data quality, how to reach difficult target groups, how to design a survey to maximize response, and ethical issues that need to be considered. Innovative applications such as the use of biomarkers and eye-tracking techniques are also explored. Part 1 provides an overview of Internet survey research including its methodologies, strengths, challenges, and best practices. Innovative ways to minimize sources of error are provided along with a review of mixed-mode designs, how to design a scientifically sound longitudinal panel and avoid sampling problems, and address ethical requirements in Web surveys. Part 2 focuses on advanced applications including the impact of visual design on the interpretability of survey questions, the impact survey usability has on respondents’ answers, design features that increase interaction, and how Internet surveys can be effectively used to study sensitive issues. Part 3 addresses data quality, sample selection, measurement and non-response error, and new applications for collecting online data. The issue of underrepresentation of certain groups in Internet research and the measures most effective at reducing it are also addressed. The book concludes with a discussion of the importance of paradata and the Web data collection process in general, followed by chapters with innovative experiments using eye-tracking techniques and biomarker data. This practical book appeals to practitioners from market survey research institutes and researchers in disciplines such as psychology, education, sociology, political science, health studies, marketing, economics, and business who use the Internet for data collection, but is also an ideal supplement for graduate and/or upper level undergraduate courses on (Internet) research methods and/or data collection taught in these fields.
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.
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.
A Research Primer for the Social and Behavioral Sciences provides an introductory but comprehensive overview of the research process that primarily concerns human subjects. This book discusses the methods of acquiring knowledge, importance of a well-chosen problem, review of the literature, and relationship between theory-building and hypothesis-testing. The common sources of invalidity in practice, non-experimental research types, Stevens' classification of scales, and estimation based on probabilistic sampling are also elaborated. This text likewise covers the role of computer in research, techniques for analysis of data, univariate and bivariate statistics, and assumptions underlying analysis of variance. Other topics include the canonical correlation analysis, non-parametric analysis of variance, deterministic problem analysis techniques, and common errors in presentation of findings. This publication is intended for novice investigators in the broad category of social and behavioral sciences.
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: National Research Council and Institute of Medicine
Publisher: National Academies Press
Release Date: 1998-10-23
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.
Author: David Magnusson
Publisher: Cambridge University Press
Release Date: 1990-05-25
This overview of the central issues of data quality in longitudinal research focuses on data relevant for studying individual development. The 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 endeavor by leading European scientists to discuss appropriate ways of handling various types of longitudinal data, including psychiatric data, alcohol data, and criminal data.
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.
The analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.