Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Social Statistics The Statistical Modelling Of Longitudinal Data
Download Social Statistics The Statistical Modelling Of Longitudinal Data full books in PDF, epub, and Kindle. Read online Social Statistics The Statistical Modelling Of Longitudinal Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Longitudinal Data Analysis by : Garrett Fitzmaurice
Download or read book Longitudinal Data Analysis written by Garrett Fitzmaurice and published by CRC Press. This book was released on 2008-08-11 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Book Synopsis Longitudinal Data Analysis by : Jason Newsom
Download or read book Longitudinal Data Analysis written by Jason Newsom and published by Routledge. This book was released on 2013-06-19 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistical Modelling for Social Researchers by : Roger Tarling
Download or read book Statistical Modelling for Social Researchers written by Roger Tarling and published by Routledge. This book was released on 2008-09-16 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces social researchers to all aspects of statistical modelling in an easily accessible but informative way. A website will accompany the book which will provide additional information and exercises. It is the first text to introduce the social researcher to the principles of statistical modelling and to the full range of methods available. This book describes in words rather than mathematical notation the aims and principles of statistical modelling but helpfully remains fully comprehensive.
Book Synopsis Longitudinal and Panel Data by : Edward W. Frees
Download or read book Longitudinal and Panel Data written by Edward W. Frees and published by Cambridge University Press. This book was released on 2004-08-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
Book Synopsis Modeling Longitudinal Data by : Robert E. Weiss
Download or read book Modeling Longitudinal Data written by Robert E. Weiss and published by Springer Science & Business Media. This book was released on 2006-12-06 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book features many figures and tables illustrating longitudinal data and numerous homework problems. The associated web site contains many longitudinal data sets, examples of computer code, and labs to re-enforce the material. Weiss emphasizes continuous data rather than discrete data, graphical and covariance methods, and generalizations of regression rather than generalizations of analysis of variance.
Book Synopsis Applied Longitudinal Data Analysis by : Judith D. Singer
Download or read book Applied Longitudinal Data Analysis written by Judith D. Singer and published by Oxford University Press. This book was released on 2003-03-27 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives.
Book Synopsis Longitudinal Structural Equation Modeling by : Todd D. Little
Download or read book Longitudinal Structural Equation Modeling written by Todd D. Little and published by Guilford Press. This book was released on 2013-02-26 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Longitudinal Structural Equation Modeling, Second Edition, ISBN 978-1-4625-5314-3.
Book Synopsis Latent Markov Models for Longitudinal Data by : Francesco Bartolucci
Download or read book Latent Markov Models for Longitudinal Data written by Francesco Bartolucci and published by CRC Press. This book was released on 2012-10-29 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on the authors' extensive research in the analysis of categorical longitudinal data, this book focuses on the formulation of latent Markov models and the practical use of these models. It demonstrates how to use the models in three types of analysis, with numerous examples illustrating how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB routines used for the examples are available on the authors' website.
Book Synopsis Longitudinal Analysis by : Lesa Hoffman
Download or read book Longitudinal Analysis written by Lesa Hoffman and published by Routledge. This book was released on 2015-01-30 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Survey of Statistical Network Models by : Anna Goldenberg
Download or read book A Survey of Statistical Network Models written by Anna Goldenberg and published by Now Publishers Inc. This book was released on 2010 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.
Book Synopsis Statistical Methods for Categorical Data Analysis by : Daniel Powers
Download or read book Statistical Methods for Categorical Data Analysis written by Daniel Powers and published by Emerald Group Publishing. This book was released on 2008-11-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at https://webspace.utexas.edu/dpowers/www/
Book Synopsis Longitudinal Data Analysis by : Professor Catrien C J H C J H Bijleveld
Download or read book Longitudinal Data Analysis written by Professor Catrien C J H C J H Bijleveld and published by SAGE. This book was released on 1998-10-26 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.
Download or read book Marginal Models written by Wicher Bergsma and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show. In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models. This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs.
Book Synopsis The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis by : Todd D. Little
Download or read book The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis written by Todd D. Little and published by Oxford University Press. This book was released on 2013-02-01 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
Book Synopsis Event History Analysis by : Paul David Allison
Download or read book Event History Analysis written by Paul David Allison and published by SAGE. This book was released on 1984-11 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on recent "event history" analytical methods from biostatistics, engineering, and sociology, this clear and comprehensive monograph explains how longitudinal data can be used to study the causes of deaths, crimes, wars, and many other human events. Allison shows why ordinary multiple regression is not suited to analyze event history data, and demonstrates how innovative regression - like methods can overcome this problem. He then discusses the particular new methods that social scientists should find useful.
Book Synopsis Latent Curve Models by : Kenneth A. Bollen
Download or read book Latent Curve Models written by Kenneth A. Bollen and published by John Wiley & Sons. This book was released on 2005-12-23 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple regression-based procedures that are useful in the early stages of LCMs, most of the presentation uses SEMs as a driving tool. This cutting-edge work includes some of the authors' recent work on the autoregressive latent trajectory model, suggests new models for method factors in multiple indicators, discusses repeated latent variable models, and establishes the identification of a variety of LCMs. This text has been thoroughly class-tested and makes extensive use of pedagogical tools to aid readers in mastering and applying LCMs quickly and easily to their own data sets. Key features include: Chapter introductions and summaries that provide a quick overview of highlights Empirical examples provided throughout that allow readers to test their newly found knowledge and discover practical applications Conclusions at the end of each chapter that stress the essential points that readers need to understand for advancement to more sophisticated topics Extensive footnoting that points the way to the primary literature for more information on particular topics With its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well as a supplemental text for courses in structural modeling. This book is an excellent aid and reference for researchers in quantitative social and behavioral sciences who need to analyze longitudinal data.
Book Synopsis Applied Longitudinal Data Analysis for Epidemiology by : Jos W. R. Twisk
Download or read book Applied Longitudinal Data Analysis for Epidemiology written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2013-05-09 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.