Download an introduction to generalized linear models 145 quantitative applications in the social sciences in pdf or read an introduction to generalized linear models 145 quantitative applications in the social sciences in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get an introduction to generalized linear models 145 quantitative applications in the social sciences in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



An Introduction To Generalized Linear Models

Author: George H. Dunteman
Publisher: SAGE
ISBN: 9780761920847
Size: 52.47 MB
Format: PDF, ePub
View: 4665
Download and Read
Do you have data that is not normally distributed and don't know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts to GLM and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets. The book provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation; includes discussion on checking model adequacy and description on how to use SAS to fit GLM; and describes the connection between survival analysis and GLM. It is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.

Modern Methods For Robust Regression

Author: Robert Andersen
Publisher: SAGE
ISBN: 1412940729
Size: 76.46 MB
Format: PDF, ePub, Mobi
View: 3095
Download and Read
Geared towards both future and practising social scientists, this book takes an applied approach and offers readers empirical examples to illustrate key concepts. It includes: applied coverage of a topic that has traditionally been discussed from a theoretical standpoint; empirical examples to illustrate key concepts; a web appendix that provides readers with the data and the R-code for the examples used in the book.

Best Practices In Quantitative Methods

Author: Jason W. Osborne
Publisher: SAGE
ISBN: 1412940656
Size: 30.23 MB
Format: PDF, Mobi
View: 6254
Download and Read
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Social Network Analysis

Author: David Knoke
Publisher: SAGE
ISBN: 1412927498
Size: 49.79 MB
Format: PDF, ePub
View: 6303
Download and Read
Providing a general overview of fundamental theoretical and methodological topics, with coverage in greater depth of selected issues, the text covers various issues in basic network concepts, data collection and network analytical methodology.

Generalized Linear Models

Author: Jeff Gill
Publisher: SAGE Publications
ISBN: 1506320244
Size: 80.53 MB
Format: PDF, ePub
View: 672
Download and Read
The author explains the theoretical underpinnings of generalized linear models so that researchers can decide how to select the best way to adapt their data for this type of analysis. Examples are provided to illustrate the application of GLM to actual data and the author includes his Web address where additional resources can be found.

Multivariate General Linear Models

Author: Richard F. Haase
Publisher: SAGE Publications
ISBN: 1483342115
Size: 60.50 MB
Format: PDF, ePub
View: 3376
Download and Read
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.

Applied Regression

Author: Michael Lewis-Beck
Publisher: SAGE Publications
ISBN: 1452208093
Size: 71.29 MB
Format: PDF, Kindle
View: 3085
Download and Read
Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.

The Association Graph And The Multigraph For Loglinear Models

Author: Harry J. Khamis
Publisher: SAGE
ISBN: 1452238952
Size: 11.61 MB
Format: PDF
View: 6799
Download and Read
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.