Regression Models for Categorical and Limited Dependent Variables

Author: J. Scott Long

Publisher: SAGE

ISBN: 9780803973749

Category: Mathematics

Page: 297

View: 9136

A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible.

Statistical models for ordinal variables

Author: Clifford C. Clogg,Edward S. Shihadeh

Publisher: Sage Publications, Inc


Category: Mathematics

Page: 192

View: 2049

"This book provides an outstanding introduction to. . . using association models developed primarily by Leo Goodman. . . . This well-written book provides a careful and generally clear introduction to association models. . . . the authors have achieved their aims well. They make a strong case for the usefulness of association models in a variety of applications. Clogg. . . and Shihadeh have provided sociologists with an introduction filled with wise advice about analyzing associations between ordinal variables." --Alan Agresti in Contemporary Sociology "This is a very useful book about. . . statistical models for ordinal variables. Reading this book. . . your reviewer was pleased to find a clear and succinct account explaining a variety of association models. . . . These models are the 'RC' models. . . . it is to statistical methods for the social sciences that this book. . . is aimed. . . . This is not a total beginner's book, however. . . and I thought the pace a little faster than leisurely. . . . a fine resource of clear description and explanation of the use of statistical models for ordinal data. . . ." --M. C. Jones in Journal of the Royal Statistical Society "This book is worthwhile reading for statisticians who have scattered training in ordinal data analysis and want to pull this training into a coherent overview. It is a fine supplement to other more mathematical books in the area. . . . After reading the book, the reader will have a clear understanding of the role of odds ratios in ordinal data analysis." --Technometrics "Includes a concise but clear review of criteria for assessing goodness-of-fit. . . . I found this volume an accessible unification of work in the area. I recommend it." --International Statistical Institute How should data involving response variables of many ordered categories be analyzed? What technique is the most useful in analyzing partially ordered variables regarded as dependent variables? Addressing these and other related concerns in social and survey research, this book carefully explores the statistical analysis of data involving dependent variables that can be coded into discrete, ordered categories. Through an analysis of ordinal variables, the authors cover the general procedures for assessing goodness-of-fit, review the independence model and the saturated model, define measures of association, demonstrate the logit version of the model and the jackknife method for contingency tables, and explain associated models for two-way tables as well as logit-type regression models.

Logistic Regression Models for Ordinal Response Variables

Author: Ann A. O'Connell

Publisher: SAGE

ISBN: 9780761929895

Category: Mathematics

Page: 107

View: 6300

Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of the cumulative (proportional) odds, continuation ratio, and adjacent category models for ordinal data. Description and examples of partial proportional odds models are also provided. This book is highly readable, with lots of examples and in-depth explanations and interpretations of model characteristics.

Statistical Modeling for Management

Author: Graeme D Hutcheson,Luiz Moutinho

Publisher: SAGE

ISBN: 1849202486

Category: Business & Economics

Page: 256

View: 8757

Bringing to life the most widely used quantitative measurements and statistical techniques in marketing, this book is packed with user-friendly descriptions, examples and study applications. The process of making marketing decisions is frequently dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems. Any student hoping to enter the world of marketing will need to show that they understand and have mastered these techniques. A bank of downloadable data sets to compliment the tables provided in the textbook are provided free for you here

Logit and Probit

Ordered and Multinomial Models

Author: Vani K. Borooah

Publisher: SAGE

ISBN: 9780761922421

Category: Mathematics

Page: 97

View: 8277

Many problems in the social sciences are amenable to analysis using the analytical tools of logit and probit models. Within this genre an important class of models are those of ordered and of multinomial models. This book explains what ordered and multinomial models are and also shows how to apply them to analyzing issues in the social sciences.

The SAGE Handbook of Quantitative Methodology for the Social Sciences

Author: David Kaplan

Publisher: SAGE Publications

ISBN: 1483365875

Category: Social Science

Page: 528

View: 4596

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.

Strength in Numbers: The Rising of Academic Statistics Departments in the U. S.

Author: Alan Agresti,Xiao-Li Meng

Publisher: Springer Science & Business Media

ISBN: 1461436494

Category: Mathematics

Page: 564

View: 982

Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success stories (such as major research accomplishments) and the occasional failure story, PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Read here all about how departments such as at Berkeley, Chicago, Harvard, and Stanford started and how they got to where they are today. The book should also be of interests to scholars in the field of disciplinary history.


The Conceptual Approach

Author: Gudmund R. Iversen,Mary Gergen

Publisher: Springer Science & Business Media

ISBN: 1461222443

Category: Mathematics

Page: 735

View: 3343

An imaginative introduction to statistics, reorienting the course towards an understanding of statistical thinking and its meaning and use in daily life and work. Gudmund Iversen and Mary Gergen bring their years of experience and insight into teaching the subject, incorporating such innovations and insights as a sustained emphasis on the process of statistical analysis and what statistics can and cannot do as well as careful exposition of the ideas of developing statistical and graphical literacy. In the spirit of contemporary pedagogy and by using technology, the authors break down the traditional barriers of statistical formulas and lengthy computations encountered by students without strong quantitative skills. Further, formulas are grouped at the end of each chapter along with related problems, and, with only algebra as a prerequisite, the book is ideal for students in the liberal arts and the behavioural and social sciences.

Logistic Regression

From Introductory to Advanced Concepts and Applications

Author: Scott Menard

Publisher: SAGE

ISBN: 1412974836

Category: Social Science

Page: 377

View: 9971

Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.

Statistical Modelling for Social Researchers

Principles and Practice

Author: Roger Tarling

Publisher: Routledge

ISBN: 1134061072

Category: Social Science

Page: 224

View: 1357

This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models. An ideal tool for postgraduate social science students, research students and practicing social researchers in universities, market research, government social research and the voluntary sector.

Interaction Effects in Logistic Regression

Author: James Jaccard

Publisher: SAGE Publications

ISBN: 1544332599

Category: Social Science

Page: 80

View: 3710

Oriented toward the applied researcher with a basic background in multiple regression and logistic regression, this book shows readers the general strategies for testing interactions in logistic regression as well as providing the tools to interpret and understand the meaning of coefficients in equations with product terms. Using completely worked-out examples, the author focuses on the interpretation of the coefficients of interactive logistic models for a wide range of scenarios encountered in the research literature. In addition, the author avoids complex formulas in favor of simple computer-based heuristics that permit the simple calculation of parameter estimates and estimated standard errors that will typically be of interest to applied researchers.

Regression Analysis

A Constructive Critique

Author: Richard A. Berk

Publisher: SAGE

ISBN: 0761929045

Category: Mathematics

Page: 259

View: 3760

Regression Analysis: A Constructive Critique identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved. Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. The emphasis on description provides readers with an insightful rethinking from the ground up of what regression analysis can do, so that readers can better match regression analysis with useful empirical questions and improved policy-related research. "An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students." --David A. Freedman, Professor of Statistics, University of California, Berkeley

Correspondence Analysis and West Mexico Archaeology

Ceramics from the Long-Glassow Collection

Author: C. Roger Nance

Publisher: UNM Press

ISBN: 0826353940

Category: History

Page: 280

View: 6243

Because the archaeology of West Mexico has received little attention from researchers, large segments of the region’s prehistoric ceramic sequences have long remained incomplete. This book goes far toward filling that gap by analyzing a collection of potsherds excavated in the 1960s and housed since then, though heretofore unanalyzed, at UCLA. The authors employ the rarely used statistical technique known as correspondence analysis to sequence the Long-Glassow collection of artifacts. The book explains how correspondence analysis works and how it can be applied in archaeology. In addition to describing the archaeological sites in north central Jalisco where the collection comes from, the authors provide an ethnohistorical overview including information on the earliest Spanish explorers to reach the sites. They sequence more than seventy ceramic types and derive a master sequence from more than ten thousand potsherds. In addition to Mesoamerican archaeologists, the audience will also include other archaeologists concerned with ceramic analysis or the application of statistics to archaeology.

Maximum Likelihood Estimation

Logic and Practice

Author: Scott R. Eliason

Publisher: SAGE

ISBN: 9780803941076

Category: Mathematics

Page: 87

View: 1036

In this volume the underlying logic and practice of maximum likelihood (ML) estimation is made clear by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses: what properties are desirable in an estimator; basic techniques for finding ML solutions; the general form of the covariance matrix for ML estimates; the sampling distribution of ML estimators; the application of ML in the normal distribution as well as in other useful distributions; and some helpful illustrations of likelihoods.

Doing Quantitative Research in the Social Sciences

An Integrated Approach to Research Design, Measurement and Statistics

Author: Thomas R Black

Publisher: SAGE

ISBN: 1446223639

Category: Social Science

Page: 768

View: 5034

This original textbook provides a comprehensive and integrated approach to using quantitative methods in the social sciences. Thomas R Black guides the student and researcher through the minefield of potential problems that may be confronted, and it is this emphasis on the practical that distinguishes his book from others which focus exclusively on either research design and measurement or statistical methods. Focusing on the design and execution of research, key topics such as planning, sampling, the design of measuring instruments, choice of statistical text and interpretation of results are examined within the context of the research process. In a lively and accessible style, the student is introduced to researc design issues alongside statistical procedures and encouraged to develop analytical and decision-making skills.

Statistical Methods for Categorical Data Analysis

Author: Daniel Powers,Yu Xie

Publisher: Emerald Group Publishing

ISBN: 9781781906590

Category: Psychology

Page: 296

View: 4217

This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. Companion website also available, at

Regression Models for Categorical Dependent Variables Using Stata, Second Edition

Author: J. Scott Long,Jeremy Freese

Publisher: Stata Press

ISBN: 1597180114

Category: Computers

Page: 527

View: 6631

After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias.

Applied Statistics for the Social and Health Sciences

Author: Rachel A. Gordon

Publisher: Routledge

ISBN: 1136484175

Category: Social Science

Page: 994

View: 2557

Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them. This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature thorough integration of teaching statistical theory with teaching data processing and analysis teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set. This book is for a two-semester course. For a one-semester course, see

Applied Ordinal Logistic Regression Using Stata

From Single-Level to Multilevel Modeling

Author: Xing Liu

Publisher: SAGE Publications

ISBN: 1483319768

Category: Social Science

Page: 552

View: 5986

The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata by Xing Liu helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.

Statistics in a Nutshell

Author: Sarah Boslaugh

Publisher: "O'Reilly Media, Inc."

ISBN: 1449316824

Category: Mathematics

Page: 569

View: 4984

A clear and concise introduction and reference for anyone new to the subject of statistics.