Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from (a) some background information about the specific approach (a short history and the main publications), each chapter then (b) describes the type of research questions the approach is able to answer, (c) provides statistical and mathematical explanations of the models used in the data analysis, (d) discusses the input and output of the programs used, and (e) provides one or more examples with typical data sets, allowing the readers to apply the programs themselves.

Social sciences -- Longitudinal studies. --- Social sciences -- Statistical methods. --- Social sciences --- Social Sciences --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Social Sciences - General --- Research --- Longitudinal method. --- Latent variables. --- Constructs, Hypothetical --- Hypothetical constructs --- Variables, Latent --- Longitudinal research --- Longitudinal studies --- Mathematics. --- Probabilities. --- Statistics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Latent structure analysis --- Multivariate analysis --- Variables (Mathematics) --- Methodology --- Distribution (Probability theory. --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Distribution functions --- Frequency distribution --- Characteristic functions --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Probability --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Social sciences - Research

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This unique book provides an overview of continuous time modeling in the behavioral and related sciences. It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable. One main issue is the dependence of discrete time parameter estimates on the chosen time interval, which leads to incomparability of results across different observation intervals. Continuous time modeling by means of differential equations offers a powerful approach for studying dynamic phenomena, yet the use of this approach in the behavioral and related sciences such as psychology, sociology, economics and medicine, is still rare. This is unfortunate, because in these fields often only a few discrete time (sampled) observations are available for analysis (e.g., daily, weekly, yearly, etc.). However, as emphasized by Rex Bergstrom, the pioneer of continuous-time modeling in econometrics, neither human beings nor the economy cease to exist in between observations. In 16 chapters, the book addresses a vast range of topics in continuous time modeling, from approaches that closely mimic traditional linear discrete time models to highly nonlinear state space modeling techniques. Each chapter describes the type of research questions and data that the approach is most suitable for, provides detailed statistical explanations of the models, and includes one or more applied examples. To allow readers to implement the various techniques directly, accompanying computer code is made available online. The book is intended as a reference work for students and scientists working with longitudinal data who have a Master's- or early PhD-level knowledge of statistics.

Social sciences (general) --- Social psychology --- Sociology --- Statistical science --- Demography --- Law --- Mathematical statistics --- Biomathematics. Biometry. Biostatistics --- Animal ethology and ecology. Sociobiology --- Computer. Automation --- cyclohexanon --- medische statistiek --- gedrag (mensen) --- gedrag (dieren) --- analytische chemie --- biochemie --- biostatistiek --- informatica --- sociale wetenschappen --- wetgeving --- statistiek --- biometrie

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)