Dependent Data In Social Sciences Research
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Dependent Data In Social Sciences Research
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Author : Mark Stemmler
language : en
Publisher:
Release Date : 2015
Dependent Data In Social Sciences Research written by Mark Stemmler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with 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.
Dependent Data In Social Sciences Research
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Author : Mark Stemmler
language : en
Publisher: Springer Nature
Release Date : 2024-10-21
Dependent Data In Social Sciences Research written by Mark Stemmler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-21 with Social Science categories.
This book covers the following subjects: 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). It 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 include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. 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.
Theory Based Data Analysis For The Social Sciences
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Author : Carol S. Aneshensel
language : en
Publisher: SAGE
Release Date : 2013
Theory Based Data Analysis For The Social Sciences written by Carol S. Aneshensel and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Reference categories.
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Introduction To Quantitative Data Analysis In The Behavioral And Social Sciences
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Author : Michael J. Albers
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-21
Introduction To Quantitative Data Analysis In The Behavioral And Social Sciences written by Michael J. Albers and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-21 with Mathematics categories.
Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.
Using Statistical Methods In Social Science Research
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Author : Soleman H. Abu-Bader
language : en
Publisher:
Release Date : 2021
Using Statistical Methods In Social Science Research written by Soleman H. Abu-Bader and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Psychology categories.
Using Statistical Methods in Social Science Research, Third Edition is the user-friendly text every student needs for analyzing and making sense of quantitative data. With over 20 years of experience teaching statistics, Soleman H. Abu-Bader provides an accessible, step-by-step description of the process needed to organize data, choose a test or statistical technique, analyze, interpret, and report research findings. The book begins with an overview of research and statistical terms, followed by an explanation of basic descriptive statistics. It then focuses on the purpose, rationale, and assumptions made by each test, such as Pearson's correlation, student's t-tests, analysis of variances, and simple linear regression, among others. The book also provides a wealth of research examples that clearly display the applicability and function of these tests in real-world practice. In a separate appendix, the author provides a step-by-step process for calculating each test for those who still like to understand the mathematical formulas behind these processes.
Applied Panel Data Analysis For Economic And Social Surveys
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Author : Hans-Jürgen Andreß
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-24
Applied Panel Data Analysis For Economic And Social Surveys written by Hans-Jürgen Andreß and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-24 with Social Science categories.
Many economic and social surveys are designed as panel studies, which provide important data for describing social changes and testing causal relations between social phenomena. This textbook shows how to manage, describe, and model these kinds of data. It presents models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All statistical methods are explained in an application-centered style using research examples from scholarly journals, which can be replicated by the reader through data provided on the accompanying website. As all models are compared to each other, it provides valuable assistance with choosing the right model in applied research. The textbook is directed at master and doctoral students as well as applied researchers in the social sciences, psychology, business administration and economics. Readers should be familiar with linear regression and have a good understanding of ordinary least squares estimation.
Marginal Models
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Author : Wicher Bergsma
language : en
Publisher: Springer
Release Date : 2009-04-06
Marginal Models written by Wicher Bergsma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-06 with Science categories.
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.
Data Protection And Social Science Research
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Author : Ekkehard Mochmann
language : en
Publisher: Ardent Media
Release Date : 1979
Data Protection And Social Science Research written by Ekkehard Mochmann and has been published by Ardent Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Social Science categories.
The Behavioral And Social Sciences
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 1988-02-01
The Behavioral And Social Sciences written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-02-01 with Science categories.
This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.
Approaches And Processes Of Social Science Research
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Author : Tshabangu, Icarbord
language : en
Publisher: IGI Global
Release Date : 2020-12-18
Approaches And Processes Of Social Science Research written by Tshabangu, Icarbord and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with Social Science categories.
For the social sciences, the approach and processes in research are quite different. The type of evidence that social scientists can collect is often very dependent on the method that has been used to gather the data. The type of findings that can be discussed are often not straightforward at all, and no easy comparison can be made with the natural sciences, although this is not impossible. The methodology in the social sciences has the same role as technology and lab techniques in the natural sciences as these need to be developed rapidly to account for the increasing complexity of the natural objects to be studied. The methodologies in the social sciences need to go through an intense period of critique, reflection, and reformulation to consider the complexity of social issues under investigation. Therefore, the area of social sciences research and methodologies should continually be studied to advance the field. Approaches and Processes of Social Science Research presents new research methodologies in the social science field and aims at providing a broad introduction to the methodology of social research in its main theoretical foundations as well as in its practical applications. Readers will develop a critical thinking attitude about social problems which in turn will sharpen their analytic approach to research. This book includes four main parts: philosophical perspectives, strategies for conducting research, common approaches for handling and collecting data, and critical aspects of research writing throughout the process. While highlighting topics such as critical theory in research, ethical issues, research processes, data analysis, and more, this book is ideal for researchers in the social sciences and practitioners, stakeholders, academicians, and students interested in deepening their understanding of the ideas and the practices of social science research.