Contemporary Issues In Exploratory Data Mining In The Behavioral Sciences

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Contemporary Issues In Exploratory Data Mining In The Behavioral Sciences

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Author : John J. McArdle
language : en
Publisher: Routledge
Release Date : 2013-08-15

Contemporary Issues In Exploratory Data Mining In The Behavioral Sciences written by John J. McArdle and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-15 with Psychology categories.

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.

Contemporary Issues In Exploratory Data Mining In The Behavioral Sciences

DOWNLOAD
Author : John J. McArdle
language : en
Publisher: Routledge
Release Date : 2013-08-15

Contemporary Issues In Exploratory Data Mining In The Behavioral Sciences written by John J. McArdle and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-15 with Psychology categories.

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.

Dependent Data In Social Sciences Research

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Author : Mark Stemmler
language : en
Publisher: Springer
Release Date : 2015-10-19

Dependent Data In Social Sciences Research written by Mark Stemmler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-19 with Social Science categories.

This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

Machine Learning For Social And Behavioral Research

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Author : Ross Jacobucci
language : en
Publisher: Guilford Publications
Release Date : 2023-07-17

Machine Learning For Social And Behavioral Research written by Ross Jacobucci and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-17 with Business & Economics categories.

Today's social and behavioral researchers increasingly need to know: "What do I do with all this data?" This book provides the skills needed to analyze and report large, complex data sets using machine learning tools, and to understand published machine learning articles. Techniques are demonstrated using actual data (Big 5 Inventory, early childhood learning, and more), with a focus on the interplay of statistical algorithm, data, and theory. The identification of heterogeneity, measurement error, regularization, and decision trees are also emphasized. The book covers basic principles as well as a range of methods for analyzing univariate and multivariate data (factor analysis, structural equation models, and mixed-effects-models). Analysis of text and social network data is also addressed. End-of-chapter "Computational Time and Resources" sections include discussions of key R packages; the companion website provides R programming scripts and data for the book's examples.

Situating Children Of Migrants Across Borders And Origins

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Author : Claudio Bolzman
language : en
Publisher: Springer
Release Date : 2017-10-25

Situating Children Of Migrants Across Borders And Origins written by Claudio Bolzman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-25 with Social Science categories.

This open access wide-ranging collation of papers examines a host of issues in studying second-generation immigrants, their life courses, and their relations with older generations. Tightly focused on methodological aspects, both quantitative and qualitative, the volume features the work of authors from numerous countries, from differing disciplines, and approaches. A key addition in a corpus of literature which has until now been restricted to studying the childhood, adolescence and youth of the children of immigrants, the material includes analysis of longitudinal and transnational efforts to address challenges such as defining the population to be studied, and the difficulties of follow-up research that spans both time and geographic space. In addition to perceptive reviews of extant literature, chapters also detail work in surveying the children of immigrants in Europe, the USA, and elsewhere. Authors address key questions such as the complexities of surveying each generation in families where parents have migrated and left children in their country of origin, and the epistemological advances in methodology which now challenge assumptions based on the Westphalian nation-state paradigm. The book is in part an outgrowth of temporal factors (immigrants’ children are now reaching adulthood in more significant numbers), but also reflects the added sophistication and sensitivity of social science surveys. In linking theoretical and methodological factors, it shows just how much the study of these second generations, and their families, can be enriched by evolving methodologies.​This book is open access under a CC BY license

Applying The Rasch Model In Social Sciences Using R

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Author : Iasonas Lamprianou
language : en
Publisher: Routledge
Release Date : 2019-12-12

Applying The Rasch Model In Social Sciences Using R written by Iasonas Lamprianou and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-12 with Psychology categories.

This unique text provides a step-by-step beginner’s guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable ("latent") variables. Each chapter is devoted to one popular Rasch model, ranging from the least to the most complex. Through a freely available and user-friendly package, BlueSky Statistics, Lamprianou offers a range of options for presenting results, critically examines the strengths and weaknesses of applying the Rasch model in each instance, and suggests more effective methodologies where applicable. With a focus on simple software code which does not assume extensive mathematical knowledge, the reader is initially introduced to the so-called simple Rasch Model to construct a "political activism" variable out of a group of dichotomously scored questions. In subsequent chapters, the book covers everything from the Rating Scale to the Many-facets Rasch model. The final chapter even showcases a complete mock manuscript, demonstrating how a Rasch-based paper on the identification of online hate speech should look like. Combining theoretical rigor and real-world examples with empirical datasets from published papers, this book is essential reading for students and researchers alike who aspire to use Rasch models in their research.

Longitudinal Multivariate Psychology

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Author : Emilio Ferrer
language : en
Publisher: Routledge
Release Date : 2018-10-09

Longitudinal Multivariate Psychology written by Emilio Ferrer and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-09 with Psychology categories.

This volume presents a collection of chapters focused on the study of multivariate change. As people develop and change, multivariate measurement of that change and analysis of those measures can illuminate the regularities in the trajectories of individual development, as well as time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social sciences, models of change have become increasingly important. This collection focuses on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes. The volume is divided into three major sections: Extension of latent change models, Measurement and testing issues in longitudinal modeling, and Novel applications of multivariate longitudinal methodology. It is intended for advanced students and researchers interested in learning about state-of-the-art techniques for longitudinal data analysis, as well as understanding the history and development of such techniques.

Multilevel Analysis

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Author : Joop Hox
language : en
Publisher: Routledge
Release Date : 2017-09-14

Multilevel Analysis written by Joop Hox and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-14 with Psychology categories.

Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.

Multilevel And Longitudinal Modeling With Ibm Spss

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Author : Ronald H. Heck
language : en
Publisher: Routledge
Release Date : 2022-04-11

Multilevel And Longitudinal Modeling With Ibm Spss written by Ronald H. Heck and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-11 with Psychology categories.

Multilevel and Longitudinal Modeling with IBM SPSS, Third Edition, demonstrates how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Versions 25-27. Annotated screenshots with all relevant output provide readers with a step-by-step understanding of each technique as they are shown how to navigate the program. Throughout, diagnostic tools, data management issues, and related graphics are introduced. SPSS commands show the flow of the menu structure and how to facilitate model building, while annotated syntax is also available for those who prefer this approach. Extended examples illustrating the logic of model development and evaluation are included throughout the book, demonstrating the context and rationale of the research questions and the steps around which the analyses are structured. The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques that facilitate working with multilevel, longitudinal, or cross-classified data sets. The next few chapters introduce the basics of multilevel modeling, developing a multilevel model, extensions of the basic two-level model (e.g., three-level models, models for binary and ordinal outcomes), and troubleshooting techniques for everyday-use programming and modeling problems along with potential solutions. Models for investigating individual and organizational change are next developed, followed by models with multivariate outcomes and, finally, models with cross-classified and multiple membership data structures. The book concludes with thoughts about ways to expand on the various multilevel and longitudinal modeling techniques introduced and issues (e.g., missing data, sample weights) to keep in mind in conducting multilevel analyses. Key features of the third edition: Thoroughly updated throughout to reflect IBM SPSS Versions 26-27. Introduction to fixed-effects regression for examining change over time where random-effects modeling may not be an optimal choice. Additional treatment of key topics specifically aligned with multilevel modeling (e.g., models with binary and ordinal outcomes). Expanded coverage of models with cross-classified and multiple membership data structures. Added discussion on model checking for improvement (e.g., examining residuals, locating outliers). Further discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures. Supported by online data sets, the book's practical approach makes it an essential text for graduate-level courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in departments of business, education, health, psychology, and sociology. The book will also prove appealing to researchers in these fields. The book is designed to provide an excellent supplement to Heck and Thomas's An Introduction to Multilevel Modeling Techniques, Fourth Edition; however, it can also be used with any multilevel or longitudinal modeling book or as a stand-alone text.

D Scoring Method Of Measurement

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Author : Dimiter Dimitrov
language : en
Publisher: Taylor & Francis
Release Date : 2023-07-18

D Scoring Method Of Measurement written by Dimiter Dimitrov and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-18 with Education categories.

D-scoring Method of Measurement presents a unified framework of classical and latent measurement referred to as D-scoring method of measurement (DSM). Provided are detailed descriptions of DSM procedures and illustrative examples of how to apply the DSM in various scenarios of measurement. The DSM is designed to combine merits of the traditional CTT and IRT for the purpose of transparency, ease of interpretations, computational simplicity of test scoring and scaling, and practical efficiency, particularly in large-scale assessments. Through detailed descriptions of DSM procedures, this book shows how practical applications of such procedures are facilitated by the inclusion of operationalized guidance for their execution using the computer program DELTA for DSM-based scoring, equating, and item analysis of test data. In doing so, the book shows how DSM procedures can be readily translated into computer source codes for other popular software packages such as R. D-scoring Method of Measurement equips researchers and practitioners in the field of educational and psychological measurement with a comprehensive understanding of the DSM as a unified framework of classical and latent scoring, equating, and psychometric analysis.