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An Introduction To Models In The Social Sciences
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Book Synopsis An Introduction to Models in the Social Sciences by : Charles A. Lave
Download or read book An Introduction to Models in the Social Sciences written by Charles A. Lave and published by University Press of America. This book was released on 1993 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is a model? How do you construct one? What are some common models in the social sciences? How can models be applied in new situations? What makes a model good? Focusing on answers to these and related questions, this multidisciplinary introduction to model building in the social sciences formulates interesting problems that involve students in creative model building and the process of invention. The book describes models of individual choice, exchange, adaptation, and diffusion. Throughout, student participation in analytical thinking is encouraged. Originally published in 1975 by HarperCollins Publishers.
Book Synopsis Formal Modeling in Social Science by : Carol Mershon
Download or read book Formal Modeling in Social Science written by Carol Mershon and published by University of Michigan Press. This book was released on 2019-09-03 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: A formal model in the social sciences builds explanations when it structures the reasoning underlying a theoretical argument, opens venues for controlled experimentation, and can lead to hypotheses. Yet more importantly, models evaluate theory, build theory, and enhance conjectures. Formal Modeling in Social Science addresses the varied helpful roles of formal models and goes further to take up more fundamental considerations of epistemology and methodology. The authors integrate the exposition of the epistemology and the methodology of modeling and argue that these two reinforce each other. They illustrate the process of designing an original model suited to the puzzle at hand, using multiple methods in diverse substantive areas of inquiry. The authors also emphasize the crucial, though underappreciated, role of a narrative in the progression from theory to model. Transparency of assumptions and steps in a model means that any analyst will reach equivalent predictions whenever she replicates the argument. Hence, models enable theoretical replication, essential in the accumulation of knowledge. Formal Modeling in Social Science speaks to scholars in different career stages and disciplines and with varying expertise in modeling.
Book Synopsis Spatial Regression Models for the Social Sciences by : Guangqing Chi
Download or read book Spatial Regression Models for the Social Sciences written by Guangqing Chi and published by SAGE Publications. This book was released on 2019-03-06 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Space and geography are important aspects of social science research in fields such as criminology, sociology, political science, and public health. Many social scientists are interested in the spatial clustering of various behaviors and events. There has been a rapid development of interest in regression methods for analyzing spatial data over recent years, but little available on the topic that is aimed at graduate students and advanced undergraduate classes in the social sciences (most texts are for the natural sciences, or regional science, or economics, and require a good understanding of advanced statistics and probability theory). Spatial Regression Models for the Social Sciences fills the gap, and focuses on the methods that are commonly used by social scientists. Each spatial regression method is introduced in the same way. Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it, by connecting it to social science research topics. They try to avoid mathematical formulas and symbols as much as possible. Secondly, throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us. Spatial Regression Models for the Social Sciences provides comprehensive coverage of spatial regression methods for social scientists and introduces the methods in an easy-to-follow manner.
Book Synopsis Quantitative Social Science by : Kosuke Imai
Download or read book Quantitative Social Science written by Kosuke Imai and published by Princeton University Press. This book was released on 2021-03-16 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
Book Synopsis How to Build Social Science Theories by : Pamela J. Shoemaker
Download or read book How to Build Social Science Theories written by Pamela J. Shoemaker and published by SAGE Publications. This book was released on 2003-12-10 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: As straightforward as its title, How to Build Social Science Theories sidesteps the well-traveled road of theoretical examination by demonstrating how new theories originate and how they are elaborated. Essential reading for students of social science research, this book traces theories from their most rudimentary building blocks (terminology and definitions) through multivariable theoretical statements, models, the role of creativity in theory building, and how theories are used and evaluated. Authors Pamela J. Shoemaker, James William Tankard, Jr., and Dominic L. Lasorsa intend to improve research in many areas of the social sciences by making research more theory-based and theory-oriented. The book begins with a discussion of concepts and their theoretical and operational definitions. It then proceeds to theoretical statements, including hypotheses, assumptions, and propositions. Theoretical statements need theoretical linkages and operational linkages; this discussion begins with bivariate relationships, as well as three-variable, four-variable, and further multivariate relationships. The authors also devote chapters to the creative component of theory-building and how to evaluate theories.
Book Synopsis An Introduction to Mathematical Models in the Social and Life Sciences by : Michael Olinick
Download or read book An Introduction to Mathematical Models in the Social and Life Sciences written by Michael Olinick and published by Addison Wesley Publishing Company. This book was released on 1978 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Modeling and Inference for Social Science by : Sean Gailmard
Download or read book Statistical Modeling and Inference for Social Science written by Sean Gailmard and published by Cambridge University Press. This book was released on 2014-06-09 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.
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 Publications. This book was released on 2023-12-27 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beloved for its engaging, conversational style, this valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book’s figures. New to This Edition: *Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux. *Chapter on longitudinal mixture modeling, with Whitney Moore. *Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne. *Chapter on Bayesian SEM, with Mauricio Garnier. *Revised throughout with new developments and discussions, such as how to test models of experimental effects.
Book Synopsis Models and Modeling in the Sciences by : Stephen M. Downes
Download or read book Models and Modeling in the Sciences written by Stephen M. Downes and published by Routledge. This book was released on 2020-07-09 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, Stephen M. Downes explores the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. Readers learn that paying attention to models plays a crucial role in appraising scientific work. This book first presents a wide range of models from a number of different scientific disciplines. After assembling some illustrative examples, Downes demonstrates how models shed light on many perennial issues in philosophy of science and in philosophy in general. Reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when readers confront the question, "What makes for a good (or bad) model?" All examples from the sciences and positions in the philosophy of science are presented in an accessible manner. The book is suitable for undergraduates with minimal experience in philosophy and an introductory undergraduate experience in science. Key features: The book serves as a highly accessible philosophical introduction to models and modeling in the sciences, presenting all philosophical and scientific issues in a nontechnical manner. Students and other readers learn to practice philosophy of science by starting with clear examples taken directly from the sciences. While not comprehensive, this book introduces the reader to a wide range of views on key issues in the philosophy of science.
Book Synopsis Causal Models in the Social Sciences by : Jr. Blalock
Download or read book Causal Models in the Social Sciences written by Jr. Blalock and published by Routledge. This book was released on 2017-07-28 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causal models are formal theories stating the relationships between precisely defined variables, and have become an indispensable tool of the social scientist. This collection of articles is a course book on the causal modeling approach to theory construction and data analysis. H. M. Blalock, Jr. summarizes the then-current developments in causal model utilization in sociology, political science, economics, and other disciplines. This book provides a comprehensive multidisciplinary picture of the work on causal models. It seeks to address the problem of measurement in the social sciences and to link theory and research through the development of causal models.Organized into five sections (Simple Recursive Models, Path Analysis, Simultaneous Equations Techniques, The Causal Approach to Measurement Error, and Other Complications), this volume contains twenty-seven articles (eight of which were specially commissioned). Each section begins with an introduction explaining the concepts to be covered in the section and links them to the larger subject. It provides a general overview of the theory and application of causal modeling.Blalock argues for the development of theoretical models that can be operationalized and provide verifiable predictions. Many of the discussions of this subject that occur in other literature are too technical for most social scientists and other scholars who lack a strong background in mathematics. This book attempts to integrate a few of the less technical papers written by econometricians such as Koopmans, Wold, Strotz, and Fisher with discussions of causal approaches in the social and biological sciences. This classic text by Blalock is a valuable source of material for those interested in the issue of measurement in the social sciences and the construction of mathematical models.
Book Synopsis Introduction to Computational Social Science by : Claudio Cioffi-Revilla
Download or read book Introduction to Computational Social Science written by Claudio Cioffi-Revilla and published by Springer. This book was released on 2017-06-29 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.
Book Synopsis An Introduction to Generalized Linear Models by : George H. Dunteman
Download or read book An Introduction to Generalized Linear Models written by George H. Dunteman and published by SAGE. This book was released on 2006 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a thorough introduction to generalized linear models (GLM), exponential family distribution & maximum likelihood estimation, this book includes discussion on checking model adequacy & description on how to use a popular statistical software programme, SAS, to fit GLM.
Book Synopsis Introduction to the Social Sciences (RLE Social Theory) by : Maurice Duverger
Download or read book Introduction to the Social Sciences (RLE Social Theory) written by Maurice Duverger and published by Routledge. This book was released on 2020-09-10 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Professor Duverger at last provides the student with an overall view of the methodology of the social sciences. He briefly traces the origin of the notion of a social science, showing how it emerged from social philosophy. Its essential elements and pre-conditions are described; the splintering of social science into specialist disciplines is explained, and the need for a general sociology confirmed. The techniques of observation used by social scientists are dealt with in some detail and the unity of the social sciences is illustrated by examples of the universal application of these techniques. Documentary evidence in its various forms are described along with the basic analytical techniques, including quantitative methods and content analysis. Other methods of gathering information through polls, interviews, attitude scales and participant observation are all described. Professor Duverger brings together the different kinds of analysis used to assess the information thus gathered. Arguing that observing and theorizing are not two different stages or levels of research, he examines the practical value and difficulties of general sociological theories, partial theories and models and working hypotheses. He both describes and assesses the limitations of experiment and the scope of comparative methods in the social sciences. He then gives elementary instructions for using and assessing the value of mathematical techniques. The possibilities of presenting social phenomena through graphs and charts are also explored. There are useful book lists and diagrams.
Book Synopsis Dynamic Modeling by : R. Robert Huckfeldt
Download or read book Dynamic Modeling written by R. Robert Huckfeldt and published by . This book was released on 1982 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Covariance Structure Models by : J. Scott Long
Download or read book Covariance Structure Models written by J. Scott Long and published by SAGE Publications, Incorporated. This book was released on 1983-09 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: While many readers may be unfamiliar with the full complexity of the covariance structure model, many may have mastered at least one of its two components - each of which is a powerful and well-known statistical technique in its own right. The first is the confirmatory factor model frequently used in psychometrics; the second, the structural equation model, is familiar to econometricians. The discussion in this volume will be particularly useful for estimating models with equality constraints and correlated errors across some but not all equations. The final chapter includes a guide to appropriate software packages.
Book Synopsis Approaches and Methodologies in the Social Sciences by : Donatella Della Porta
Download or read book Approaches and Methodologies in the Social Sciences written by Donatella Della Porta and published by Cambridge University Press. This book was released on 2008-08-28 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revolutionary textbook introducing masters and doctoral students to the major research approaches and methodologies in the social sciences. Written by an outstanding set of scholars, and derived from successful course teaching, this volume will empower students to choose their own approach to research, to justify this approach, and to situate it within the discipline. It addresses questions of ontology, epistemology and philosophy of social science, and proceeds to issues of methodology and research design essential for producing a good research proposal. It also introduces researchers to the main issues of debate and contention in the methodology of social sciences, identifying commonalities, historic continuities and genuine differences.
Book Synopsis Statistical Models and Causal Inference by : David A. Freedman
Download or read book Statistical Models and Causal Inference written by David A. Freedman and published by Cambridge University Press. This book was released on 2010 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
