Pooled Time Series Analysis

Author: Lois W. Sayrs
Publisher: SAGE
ISBN: 9780803931602
Format: PDF, ePub, Mobi
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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.

Introduction to Time Series Analysis

Author: Mark Pickup
Publisher: SAGE Publications
ISBN: 1483324540
Format: PDF, ePub, Docs
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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

Abortion Rates in the United States

Author: Matthew E. Wetstein
Publisher: SUNY Press
ISBN: 9780791428481
Format: PDF, Mobi
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Demonstrates that individual state policies on abortion closely reflect public opinion in that state and affect abortion rates, whereas national policy and policy changes have no real effect on abortion rates.

Fractal Analysis

Author: Clifford Brown
Publisher: SAGE
ISBN: 1412971659
Format: PDF, Mobi
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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
Publisher: SAGE Publications
ISBN: 1483342638
Format: PDF
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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

Multivariate General Linear Models

Author: Richard F. Haase
Publisher: SAGE Publications
ISBN: 1483342115
Format: PDF, Mobi
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Multivariate General Linear Models is an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data, and introduces multivariate linear model analysis as a generalization of the univariate model. The author focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy. The volume concludes with a discussion of canonical correlation analysis that is shown to subsume all the multivariate procedures discussed in previous chapters. The analyses are illustrated throughout the text with three running examples drawing from several disciples, including personnel psychology, anthropology, environmental epidemiology, and neuropsychology.

Nonrecursive Models

Author: Pamela Paxton
Publisher: SAGE Publications
ISBN: 1412974445
Format: PDF
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Nonrecursive Models provides explicit guidance to researchers on the estimation and assessment of nonrecursive simultaneous equation models in a clear, condensed and precise form. It guides readers through the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly interpret results.

The Association Graph and the Multigraph for Loglinear Models

Author: Harry J. Khamis
Publisher: SAGE
ISBN: 1452238952
Format: PDF, Kindle
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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.