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Maximum Likelihood For Social Science
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Book Synopsis Maximum Likelihood for Social Science by : Michael D. Ward
Download or read book Maximum Likelihood for Social Science written by Michael D. Ward and published by Cambridge University Press. This book was released on 2018-11-22 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.
Book Synopsis Maximum Likelihood Estimation by : Scott R. Eliason
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE. This book was released on 1993 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Book Synopsis Unifying Political Methodology by : Gary King
Download or read book Unifying Political Methodology written by Gary King and published by University of Michigan Press. This book was released on 1998-06-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: DIVArgues that likelihood theory is a unifying approach to statistical modeling in political science /div
Book Synopsis Regression Models for Categorical and Limited Dependent Variables by : J. Scott Long
Download or read book Regression Models for Categorical and Limited Dependent Variables written by J. Scott Long and published by SAGE. This book was released on 1997-01-09 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
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 Regression Diagnostics by : John Fox
Download or read book Regression Diagnostics written by John Fox and published by SAGE Publications. This book was released on 2019-12-09 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website.
Book Synopsis The SAGE Encyclopedia of Social Science Research Methods by : Michael Lewis-Beck
Download or read book The SAGE Encyclopedia of Social Science Research Methods written by Michael Lewis-Beck and published by SAGE. This book was released on 2004 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Book Synopsis Research Methodology in Social Science by : Arvind Kumar
Download or read book Research Methodology in Social Science written by Arvind Kumar and published by Sarup & Sons. This book was released on 2002 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Yet Research May Be Regarded As A Useful Form Of Activity. Research, In The Sense Of Development, Elaboration And Refinement Of Principles, Together With The Collection And Use Of Empirical Materials To Help In These Processes, Is One Of Die Highest Activities Of A University And One In Which All Its Professors Should Be Engaged. Research Need Not Be Thought Of As A Special Prerogative Of Young Men And Women Preparing Themselves For A Higher Degree. Nobody Needs The Permission Of A University To Do Research And Many Of The Great Scholars Did Not Any Research In The Ordinary Sense Of The Term. Yet They Succeeded In Contributing Significantly To The Existing Realms Of Knowledge. Research Is A Matter Of Realising A Question And Then Trying To Find An Answer. In Other Words, Research Means A Sort Of Investigation Describing The Fact That Some Problem Is Being Investigated To Shed For Generalization. Therefore, Research Is The Activity Of Solving Problem Which Adds New Knowledge And Developing Of Theory As Well As Gathering Of Evidence To Test Generalization.In View Of This, The Present Attempt Is Made To Describe The Different Aspects Of Research Generally Being Conducted By The Social Scientists And It Is Hoped That It Will Be Of Great Use For All Those Concerned With Social Research.
Book Synopsis Statistical Inference as Severe Testing by : Deborah G. Mayo
Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Book Synopsis Information Bounds and Nonparametric Maximum Likelihood Estimation by : P. Groeneboom
Download or read book Information Bounds and Nonparametric Maximum Likelihood Estimation written by P. Groeneboom and published by Springer Science & Business Media. This book was released on 1992-07-31 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the lecture notes for a DMV course presented by the authors at Gunzburg, Germany, in September, 1990. In the course we sketched the theory of information bounds for non parametric and semiparametric models, and developed the theory of non parametric maximum likelihood estimation in several particular inverse problems: interval censoring and deconvolution models. Part I, based on Jon Wellner's lectures, gives a brief sketch of information lower bound theory: Hajek's convolution theorem and extensions, useful minimax bounds for parametric problems due to Ibragimov and Has'minskii, and a recent result characterizing differentiable functionals due to van der Vaart (1991). The differentiability theorem is illustrated with the examples of interval censoring and deconvolution (which are pursued from the estimation perspective in part II). The differentiability theorem gives a way of clearly distinguishing situations in which 1 2 the parameter of interest can be estimated at rate n / and situations in which this is not the case. However it says nothing about which rates to expect when the functional is not differentiable. Even the casual reader will notice that several models are introduced, but not pursued in any detail; many problems remain. Part II, based on Piet Groeneboom's lectures, focuses on non parametric maximum likelihood estimates (NPMLE's) for certain inverse problems. The first chapter deals with the interval censoring problem.
Book Synopsis The SAGE Handbook of Quantitative Methodology for the Social Sciences by : David Kaplan
Download or read book The SAGE Handbook of Quantitative Methodology for the Social Sciences written by David Kaplan and published by SAGE Publications. This book was released on 2004-06-21 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: Click ′Additional Materials′ for downloadable samples "The 24 chapters in this Handbook span a wide range of topics, presenting the latest quantitative developments in scaling theory, measurement, categorical data analysis, multilevel models, latent variable models, and foundational issues. Each chapter reviews the historical context for the topic and then describes current work, including illustrative examples where appropriate. The level of presentation throughout the book is detailed enough to convey genuine understanding without overwhelming the reader with technical material. Ample references are given for readers who wish to pursue topics in more detail. The book will appeal to both researchers who wish to update their knowledge of specific quantitative methods, and students who wish to have an integrated survey of state-of- the-art quantitative methods." —Roger E. Millsap, Arizona State University "This handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential reference for social science researchers as an introduction to methods and quantitative concepts of great use." —Irini Moustaki, London School of Economics, U.K. "David Kaplan and SAGE Publications are to be congratulated on the development of a new handbook on quantitative methods for the social sciences. The Handbook is more than a set of methodologies, it is a journey. This methodological journey allows the reader to experience scaling, tests and measurement, and statistical methodologies applied to categorical, multilevel, and latent variables. The journey concludes with a number of philosophical issues of interest to researchers in the social sciences. The new Handbook is a must purchase." —Neil H. Timm, University of Pittsburgh The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource. The handbook is divided into six sections: • Scaling • Testing and Measurement • Models for Categorical Data • Models for Multilevel Data • Models for Latent Variables • Foundational Issues These sections, comprising twenty-four chapters, address topics in scaling and measurement, advances in statistical modeling methodologies, and broad philosophical themes and foundational issues that transcend many of the quantitative methodologies covered in the book. The Handbook is indispensable to the teaching, study, and research of quantitative methods and will enable readers to develop a level of understanding of statistical techniques commensurate with the most recent, state-of-the-art, theoretical developments in the field. It provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method, depending on the data and distinct research situation.
Book Synopsis Maximum Likelihood Estimation for Sample Surveys by : Raymond L. Chambers
Download or read book Maximum Likelihood Estimation for Sample Surveys written by Raymond L. Chambers and published by CRC Press. This book was released on 2012-05-02 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to biased and inefficient estimates. Maximum Likelihood Estimation for Sample Surveys presents an overview of likelihood methods for the analysis of sample survey data that account for the selection methods used, and includes all necessary background material on likelihood inference. It covers a range of data types, including multilevel data, and is illustrated by many worked examples using tractable and widely used models. It also discusses more advanced topics, such as combining data, non-response, and informative sampling. The book presents and develops a likelihood approach for fitting models to sample survey data. It explores and explains how the approach works in tractable though widely used models for which we can make considerable analytic progress. For less tractable models numerical methods are ultimately needed to compute the score and information functions and to compute the maximum likelihood estimates of the model parameters. For these models, the book shows what has to be done conceptually to develop analyses to the point that numerical methods can be applied. Designed for statisticians who are interested in the general theory of statistics, Maximum Likelihood Estimation for Sample Surveys is also aimed at statisticians focused on fitting models to sample survey data, as well as researchers who study relationships among variables and whose sources of data include surveys.
Book Synopsis Probability and Social Science by : Daniel Courgeau
Download or read book Probability and Social Science written by Daniel Courgeau and published by Springer Science & Business Media. This book was released on 2012-02-22 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work examines in depth the methodological relationships that probability and statistics have maintained with the social sciences from their emergence. It covers both the history of thought and current methods. First it examines in detail the history of the different paradigms and axioms for probability, from their emergence in the seventeenth century up to the most recent developments of the three major concepts: objective, subjective and logicist probability. It shows the statistical inference they permit, different applications to social sciences and the main problems they encounter. On the other side, from social sciences—particularly population sciences—to probability, it shows the different uses they made of probabilistic concepts during their history, from the seventeenth century, according to their paradigms: cross-sectional, longitudinal, hierarchical, contextual and multilevel approaches. While the ties may have seemed loose at times, they have more often been very close: some advances in probability were driven by the search for answers to questions raised by the social sciences; conversely, the latter have made progress thanks to advances in probability. This dual approach sheds new light on the historical development of the social sciences and probability, and on the enduring relevance of their links. It permits also to solve a number of methodological problems encountered all along their history.
Book Synopsis Introduction to Applied Bayesian Statistics and Estimation for Social Scientists by : Scott M. Lynch
Download or read book Introduction to Applied Bayesian Statistics and Estimation for Social Scientists written by Scott M. Lynch and published by Springer Science & Business Media. This book was released on 2007-06-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.
Book Synopsis In the Interest of Others by : John S. Ahlquist
Download or read book In the Interest of Others written by John S. Ahlquist and published by Princeton University Press. This book was released on 2013-09-08 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking study of labor unions that advances a new theory of organizational leadership and governance In the Interest of Others develops a new theory of organizational leadership and governance to explain why some organizations expand their scope of action in ways that do not benefit their members directly. John Ahlquist and Margaret Levi document eighty years of such activism by the International Longshore and Warehouse Union in the United States and the Waterside Workers Federation in Australia. They systematically compare the ILWU and WWF to the Teamsters and the International Longshoremen's Association, two American transport industry labor unions that actively discouraged the pursuit of political causes unrelated to their own economic interests. Drawing on a wealth of original data, Ahlquist and Levi show how activist organizations can profoundly transform the views of members about their political efficacy and the collective actions they are willing to contemplate. They find that leaders who ask for support of projects without obvious material benefits must first demonstrate their ability to deliver the goods and services members expect. These leaders must also build governance institutions that coordinate expectations about their objectives and the behavior of members. In the Interest of Others reveals how activist labor unions expand the community of fate and provoke preferences that transcend the private interests of individual members. Ahlquist and Levi then extend this logic to other membership organizations, including religious groups, political parties, and the state itself.
Book Synopsis Mathematics for Social Scientists by : Jonathan Kropko
Download or read book Mathematics for Social Scientists written by Jonathan Kropko and published by SAGE Publications. This book was released on 2015-09-09 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students’ confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students’ reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations.
Book Synopsis Designing Surveys by : Ronald F. Czaja
Download or read book Designing Surveys written by Ronald F. Czaja and published by SAGE. This book was released on 2014 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written with the needs and goals of a novice researcher in mind, this fully updated third edition provides an accurate account of how modern survey research is actually conducted. In addition to providing examples of alternative procedures, Designing Surveys shows how classic principles and recent research guide decision-making from setting the basic features of the survey through development, testing, and data collection.
