New Developments in Categorical Data Analysis for the Social and Behavioral Sciences

Author: L. Andries van der Ark,Marcel A. Croon,Klaas Sijtsma

Publisher: Psychology Press

ISBN: 1135704848

Category: Business & Economics

Page: 240

View: 3549

DOWNLOAD NOW »
Categorical data are quantified as either nominal variables--distinguishing different groups, for example, based on socio-economic status, education, and political persuasion--or ordinal variables--distinguishing levels of interest, such as the preferred politician or the preferred type of punishment for committing burglary. This new book is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets. This volume concentrates on latent class analysis and item response theory. These methods use latent variables to explain the relationships among observed categorical variables. Latent class analysis yields the classification of a group of respondents according to their pattern of scores on the categorical variables. This provides insight into the mechanisms producing the data and allows the estimation of factor structures and regression models conditional on the latent class structure. Item response theory leads to the identification of one or more ordinal or interval scales. In psychological and educational testing these scales are used for individual measurement of abilities and personality traits. The focus of this volume is applied. After a method is explained, the potential of the method for analyzing categorical data is illustrated by means of a real data example to show how it can be used effectively for solving a real data problem. These methods are accessible to researchers not trained explicitly in applied statistics. This volume appeals to researchers and advanced students in the social and behavioral sciences, including social, developmental, organizational, clinical and health psychologists, sociologists, educational and marketing researchers, and political scientists. In addition, it is of interest to those who collect data on categorical variables and are faced with the problem of how to analyze such variables--among themselves or in relation to metric variables.

Multilevel Modeling of Categorical Outcomes Using IBM SPSS

Author: Ronald H Heck,Scott Thomas,Lynn Tabata

Publisher: Routledge

ISBN: 1136672346

Category: Psychology

Page: 456

View: 5381

DOWNLOAD NOW »
This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.

Longitudinal Models in the Behavioral and Related Sciences

Author: Kees van Montfort,Johan Oud,Albert Satorra

Publisher: Psychology Press

ISBN: 9780805859133

Category: Psychology

Page: 447

View: 5231

DOWNLOAD NOW »
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.

Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences

Author: John J. McArdle,Gilbert Ritschard

Publisher: Routledge

ISBN: 1135044090

Category: Psychology

Page: 474

View: 5243

DOWNLOAD NOW »
This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM techniques in various settings. Readers are also introduced to the most popular EDM software programs. A related website at http://mephisto.unige.ch/pub/edm-book-supplement/offers color versions of the book’s figures, a supplemental paper to chapter 3, and R commands for some chapters. The results of EDM analyses can be perilous – they are often taken as predictions with little regard for cross-validating the results. This carelessness can be catastrophic in terms of money lost or patients misdiagnosed. This book addresses these concerns and advocates for the development of checks and balances for EDM analyses. Both the promises and the perils of EDM are addressed. Editors McArdle and Ritschard taught the "Exploratory Data Mining" Advanced Training Institute of the American Psychological Association (APA). All contributors are top researchers from the US and Europe. Organized into two parts--methodology and applications, the techniques covered include decision, regression, and SEM tree models, growth mixture modeling, and time based categorical sequential analysis. Some of the applications of EDM (and the corresponding data) explored include: selection to college based on risky prior academic profiles the decline of cognitive abilities in older persons global perceptions of stress in adulthood predicting mortality from demographics and cognitive abilities risk factors during pregnancy and the impact on neonatal development Intended as a reference for researchers, methodologists, and advanced students in the social and behavioral sciences including psychology, sociology, business, econometrics, and medicine, interested in learning to apply the latest exploratory data mining techniques. Prerequisites include a basic class in statistics.

Statistics and Causality

Methods for Applied Empirical Research

Author: Wolfgang Wiedermann,Alexander von Eye

Publisher: John Wiley & Sons

ISBN: 1118947053

Category: Social Science

Page: 480

View: 9088

DOWNLOAD NOW »
A one-of-a-kind guide to identifying and dealing with modern statistical developments in causality Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Research focuses on the most up-to-date developments in statistical methods in respect to causality. Illustrating the properties of statistical methods to theories of causality, the book features a summary of the latest developments in methods for statistical analysis of causality hypotheses. The book is divided into five accessible and independent parts. The first part introduces the foundations of causal structures and discusses issues associated with standard mechanistic and difference-making theories of causality. The second part features novel generalizations of methods designed to make statements concerning the direction of effects. The third part illustrates advances in Granger-causality testing and related issues. The fourth part focuses on counterfactual approaches and propensity score analysis. Finally, the fifth part presents designs for causal inference with an overview of the research designs commonly used in epidemiology. Statistics and Causality: Methods for Applied Empirical Research also includes: New statistical methodologies and approaches to causal analysis in the context of the continuing development of philosophical theories End-of-chapter bibliographies that provide references for further discussions and additional research topics Discussions on the use and applicability of software when appropriate Statistics and Causality: Methods for Applied Empirical Research is an ideal reference for practicing statisticians, applied mathematicians, psychologists, sociologists, logicians, medical professionals, epidemiologists, and educators who want to learn more about new methodologies in causal analysis. The book is also an excellent textbook for graduate-level courses in causality and qualitative logic.

Computer science and statistics

proceedings of the Sixteenth Symposium on the Interface, Atlanta, Georgia, March 1984

Author: Lynne Billard

Publisher: North Holland

ISBN: N.A

Category: Computers

Page: 296

View: 6570

DOWNLOAD NOW »

Rationality in Planning

Critical Essays on the Role of Rationality in Urban & Regional Planning

Author: Michael J. Breheny,Regional Science Association. British Section

Publisher: N.A

ISBN: 9780850861129

Category: Political Science

Page: 247

View: 7219

DOWNLOAD NOW »

Data Analysis, Machine Learning and Applications

Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7-9, 2007

Author: Christine Preisach,Hans Burkhardt,Lars Schmidt-Thieme,Reinhold Decker

Publisher: Springer Science & Business Media

ISBN: 9783540782469

Category: Computers

Page: 719

View: 3342

DOWNLOAD NOW »
Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.

Structural Equation Modeling

Foundations and Extensions

Author: David Kaplan

Publisher: SAGE

ISBN: 1412916240

Category: Mathematics

Page: 255

View: 372

DOWNLOAD NOW »
Thoroughly revised to address the recent developments that continue to shape the use of structural equation modeling (SEM) in the social and behavioural sciences, the Second Edition of Structural Equation Modeling author has restructured the book into three defined sections: - the foundations of SEM, including path analysis and factor analysis - traditional SEM for continuous latent variables, including assumption issues as well as latent growth curve modeling for continuous growth factors - SEM for categorical latent variables, including latent class analysis, Markov models (latent and mixed latent), and growth mixture modeling. Through the use of detailed, empirical examples, Kaplan demonstrates how SEM can provide a unique lens on the problems social and behavioural scientists face. The book has been enhanced with certain features that will guide the student and researcher through the foundations and critical assumptions of SEM.

An introduction to multilevel modeling techniques

Author: Ronald H. Heck,Scott Loring Thomas

Publisher: Psychology Press

ISBN: N.A

Category: Business & Economics

Page: 268

View: 3559

DOWNLOAD NOW »
This comprehensive, applied approach to multilevel analysis is distinguished by its wide range of applications relevant to the behavioral, educational, organizational, and social sciences. Univariate and multivariate models are used to understand how to design studies and analyze data. Readers are encouraged to consider what they are investigating, their data, and the strengths and limitations of each technique before selecting their approach. Numerous examples and exercises allow readers to test their understanding of the techniques. Input programs from HLM and Mplus demonstrate how to set up and run the models. A latent variable conceptual framework is emphasized to show the commonality of the approaches and to make each technique more accessible. The first section is devoted to conceptual issues underlying multilevel modeling, while the second section develops several types of multilevel analyses including univariate regression, structural equation, growth curve and latent change, and latent variable mixture modeling. The new edition features: New chapters on multilevel longitudinal and categorical models 80% new exercises and examples website at http://www.psypress.com/multilevel-modeling-techniques/ providing datasets and program setups in HLM, SPSS, Mplus, and LISREL Increased emphasis on how multilevel techniques are used to examine changes in individuals and organizations over time. Ideal for introductory graduate level courses on multilevel and/or latent variable modeling, this book is intended for students and researchers in psychology, business, education, health, and sociology interested in understanding multilevel modeling. Prerequisites include an introduction to data analysis and univariate statistics.

Encyclopedia of Business Analytics and Optimization

Author: Wang, John

Publisher: IGI Global

ISBN: 1466652039

Category: Business & Economics

Page: 2754

View: 3380

DOWNLOAD NOW »
As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.

R für Einsteiger

Einführung in die Statistiksoftware für die Sozialwissenschaften. Mit Online-Material

Author: Maike Luhmann

Publisher: N.A

ISBN: 9783621282499

Category:

Page: 336

View: 1368

DOWNLOAD NOW »