Introduction to Time Series Analysis

Author: Mark Pickup

Publisher: SAGE Publications

ISBN: 1483324540

Category: Social Science

Page: 232

View: 5568

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Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University

Time Series Analysis

With Applications in R

Author: Jonathan D. Cryer,Kung-Sik Chan

Publisher: Springer Science & Business Media

ISBN: 038775959X

Category: Mathematics

Page: 491

View: 5436

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This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.

Interrupted Time Series Analysis

Author: David McDowall,Richard McCleary,Errol Meidinger,Richard A. Hay, Jr,Professor of Criminology Law & Society and Planning Policy & Design Richard McCleary

Publisher: SAGE

ISBN: 9780803914933

Category: Social Science

Page: 96

View: 8193

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Describes ARIMA, or Box-Tiao models, widely used in the analysis of interrupted time series quasi-experiments. Assumes no statistical background beyond simple correlation.Learn more about "The Little Green Book" - QASS Series! Click Here

Multiple Time Series Models

Author: Patrick T. Brandt,John T. Williams

Publisher: SAGE

ISBN: 1412906563

Category: Mathematics

Page: 99

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Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data including simultaneous equations, ARIMA, error correction models, and vector autoregression. Authors Patrick T. Brandt and John T. Williams focus on vector autoregression (VAR) models as a generalization of these other approaches and discuss specification, estimation, and inference using these models.

The Association Graph and the Multigraph for Loglinear Models

Author: Harry J. Khamis

Publisher: SAGE

ISBN: 1452238952

Category: Mathematics

Page: 136

View: 6779

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The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.

Fractal Analysis

Author: Clifford Brown,Larry Liebovitch

Publisher: SAGE

ISBN: 1412971659

Category: Mathematics

Page: 90

View: 6702

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As one of the only texts introducing fractal analysis and the social processes involved to social science readers, this is a must-have book for those looking to gain an understanding of this area of analysis.

Assessing Inequality

Author: Lingxin Hao,Daniel Q. Naiman

Publisher: SAGE Publications

ISBN: 1483342638

Category: Social Science

Page: 160

View: 8152

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Providing basic foundations for measuring inequality from the perspective of distributional properties This monograpg reviews a set of widely used summary inequality measures, and the lesser known relative distribution method provides the basic rationale behind each measure and discusses their interconnections. It also introduces model-based decomposition of inequality over time using quantile regression. This approach enables researchers to estimate two different contributions to changes in inequality between two time points. Key Features Clear statistical explanations provide fundamental statistical basis for understanding the new modeling framework Straightforward empirical examples reinforce statistical knowledge and ready-to-use procedures Multiple approaches to assessing inequality are introduced by starting with the basic distributional property and providing connections among approaches This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as individual researchers. Learn more about "The Little Green Book" - QASS Series! Click Here

Nonrecursive Models

Endogeneity, Reciprocal Relationships, and Feedback Loops

Author: Pamela Paxton,John R. Hipp,Sandra Marquart-Pyatt

Publisher: SAGE

ISBN: 1452237867

Category: Mathematics

Page: 144

View: 3440

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Nonrecursive Models is a clear and concise introduction to the estimation and assessment of nonrecursive simultaneous equation models. This unique monograph gives practical advice on the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly interpret results.

Multivariate General Linear Models

Author: Richard F. Haase

Publisher: SAGE

ISBN: 1412972493

Category: Mathematics

Page: 216

View: 328

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This book provides a graduate level introduction to multivariate multiple regression analysis. The book can be used as a sole text for that topic, or as a supplemental text in a course that addresses a larger number of multivariate topics. The text is divided into seven short chapters. Apart from the introductory chapter giving an overview of multivariate multiple regression models, the content outline follows the classic steps required to solve multivariate general linear model problems: (a) specifying the model (b)estimating the parameters of the model (c) establishing measures of goodness of fit of the model (d) establishing test statistics and testing hypotheses about the model (e) diagnosing the adequacy of the model.

Spatial Regression Models

Author: Michael D. Ward,Kristian Skrede Gleditsch

Publisher: SAGE

ISBN: 1412954150

Category: Mathematics

Page: 99

View: 4790

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Assuming no prior knowledge this book is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on a Web site maintained by the authors.

Complexity Theory and the Social Sciences

An Introduction

Author: David Byrne

Publisher: Routledge

ISBN: 1134714734

Category: Social Science

Page: 224

View: 3789

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Chaos and complexity are the new buzz words in both science and contemporary society. The ideas they represent have enormous implications for the way we understand and engage with the world. Complexity Theory and the Social Sciences introduces students to the central ideas which surround the chaos/complexity theories. It discusses key concepts before using them as a way of investigating the nature of social research. By applying them to such familiar topics as urban studies, education and health, David Byrne allows readers new to the subject to appreciate the contribution which complexity theory can make to social research and to illuminating the crucial social issues of our day.

Pooled Time Series Analysis

Author: Lois W. Sayrs

Publisher: SAGE

ISBN: 9780803931602

Category: Mathematics

Page: 79

View: 5257

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Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross-sections). Pooled Time Series Analysis combines time series and cross-sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied. In addition, with more relevant data available this analysis technique allows the sample size to be increased, which ultimately yields a more effective study.

Internet Data Collection

Author: Samuel J. Best,Brian S. Krueger

Publisher: SAGE

ISBN: 9780761927105

Category: Computers

Page: 91

View: 4885

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Designed for researchers and students alike, the volume describes how to perform each stage of the data collection process on the Internet, including sampling, instrument design, and administration. Through the use of non-technical prose and illustrations, it details the options available, describes potential dangers in choosing them, and provides guidelines for sidestepping them. In doing so, though, it does not simply reiterate the practices of traditional communication modes, but approaches the Internet as a unique medium that necessitates its own conventions.

Applied Statistics: From Bivariate Through Multivariate Techniques

From Bivariate Through Multivariate Techniques

Author: Rebecca M. Warner

Publisher: SAGE

ISBN: 141299134X

Category: Mathematics

Page: 1172

View: 3290

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Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.

Chaos and Catastrophe Theories

Author: Courtney Brown

Publisher: SAGE

ISBN: 9780803958470

Category: Medical

Page: 77

View: 1576

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What is chaos? How can it be measured? How are the models estimated? What is catastrophe? How is it modelled? How are the models estimated? These questions are the focus of this volume. Beginning with an explanation of the differences between deterministic and probabilistic models, Brown then introduces the reader to chaotic dynamics. Other topics covered are finding settings in which chaos can be measured, estimating chaos using nonlinear least squares and specifying catastrophe models. Finally a nonlinear system of equations that models catastrophe using real survey data is estimated.

The SAGE Encyclopedia of Social Science Research Methods

Author: Michael Lewis-Beck,Alan E Bryman,Tim Futing Liao

Publisher: SAGE

ISBN: 9780761923633

Category: Social Science

Page: 1305

View: 9034

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"The first encyclopedia to cover inclusively both quantitative and qualitative research approaches, this set provides clear explanations of 1,000 methodologies, avoiding mathematical equations when possible with liberal cross-referencing and bibliographies. Each volume includes a list of works cited, and the third contains a comprehensive index and lists of person names, organizations, books, tests, software, major concepts, surveys, and methodologies."--"Reference that rocks," American Libraries, May 2005.

Nonparametric Statistics with Applications to Science and Engineering

Author: Paul H. Kvam,Brani Vidakovic

Publisher: John Wiley & Sons

ISBN: 9780470168691

Category: Mathematics

Page: 448

View: 3415

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A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.

Event History and Survival Analysis

Regression for Longitudinal Event Data

Author: Paul D. Allison

Publisher: SAGE Publications

ISBN: 148331605X

Category: Social Science

Page: 112

View: 1679

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Social scientists are interested in events and their causes. Although event histories are ideal for studying the causes of events, they typically possess two features—censoring and time-varying explanatory variables—that create major problems for standard statistical procedures. Several innovative approaches have been developed to accommodate these two peculiarities of event history data. This volume surveys these methods, concentrating on the approaches that are most useful to the social sciences. In particular, Paul D. Allison focuses on regression methods in which the occurrence of events is dependent on one or more explanatory variables. He gives attention to the statistical models that form the basis of event history analysis, and also to practical concerns such as data management, cost, and useful computer software. The Second Edition is part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which continues to serve countless students, instructors, and researchers in learning the most cutting-edge quantitative techniques.