Generalized Linear Models

Author: Jeff Gill
Publisher: SAGE Publications
ISBN: 1506320244
Size: 32.32 MB
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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.

Modern Methods For Robust Regression

Author: Robert Andersen
Publisher: SAGE
ISBN: 1412940729
Size: 34.12 MB
Format: PDF, ePub, Docs
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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.

Advances In Doctoral Research In Management

Author: Luiz Moutinho
Publisher: World Scientific
ISBN: 9814481777
Size: 22.18 MB
Format: PDF, Mobi
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Within the academic realm, doctoral research plays a vital role in the advancement of knowledge. In areas ranging from strategy and international business to marketing, finance and operations management, the contributions in this volume represent the very best in doctoral research in the field of management worldwide. This first book in the Advances in Doctoral Research in Management series includes both doctoral research papers and a section on doctoral research notes consisting of shorter versions of extended monographs. There is also a section on research methodology papers that builds awareness and provides applications of new methodological concepts, techniques and tools. Contents:Knowledge Transfer: A Review to Explore Conceptual Foundations and Research Agenda (S M Jasimuddin)Negotiating Incommensurability in Marketing Theory (M Tadajewski et al.)Explaining Ecological Product Purchase Using Consumers' Psychographic Characteristics (E Fraj et al.)Extensions of Logistic Growth Model for the Forecasting of Product Life Cycle Segments (M Sokele & V Hudek)Defensive Strategies and Consumers' Bounded Rationality: An Artificial Market Simulation (J A Mazanec et al.)A User Evaluation of Web Recommender Systems (U Bauernfeind)The Determinants of Relationship Marketing: An Application to Thermal Spas (J Antunes)Supermarket Site Assessment and the Importance of Spatial Analysis Data (A B Mendes et al.)A Framework for Corporate Crisis Management: Applications to SMEs in Australia (M Aba-Bulgu & S M N Islam)Option Games, Asymmetric Information and Merger Announcement Returns (H Pan & X Xia)Analysing Data Using GLM Models (G D Hutcheson)The Issue of Missing Values, Their Presence and Management: A Relevant Demonstration of Data Analysis in Marketing Using CaRBS (M J Beynon) Readership: Doctoral students, researchers, and academics in the field of management. Suitable as supplementary reading in doctoral programs. Keywords:Doctoral;Research;Management Methodology;Data;Analysis;Paradigm;Modeling;InternationalKey Features:A unique academic refereed outlet on doctoral research in the field of managementA key reference in the libraries of all doctoral programs

Predictive Modeling Applications In Actuarial Science Volume 1 Predictive Modeling Techniques

Author: Edward W. Frees
Publisher: Cambridge University Press
ISBN: 1139992317
Size: 18.34 MB
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Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data.

Logistic Regression Models For Ordinal Response Variables

Author: Ann A. O'Connell
Publisher: SAGE
ISBN: 9780761929895
Size: 26.71 MB
Format: PDF
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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.

The Association Graph And The Multigraph For Loglinear Models

Author: Harry J. Khamis
Publisher: SAGE
ISBN: 1452238952
Size: 56.51 MB
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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.

Interaction Effects In Linear And Generalized Linear Models

Author: Robert L. Kaufman
Publisher: SAGE Publications
ISBN: 1506365361
Size: 65.62 MB
Format: PDF
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Robert L. Kaufman's Interaction Effects in Linear and Generalized Linear Models provides comprehensive and accessible coverage of methods for interpreting interaction effects in regression-like models. There are very few books that cover interaction effects in the linear and generalized model in this depth, and the focus on applied research using Stata will make this an invaluable guide for graduate students taking quantitative methods courses in the social and behavioral sciences. The first part of the book develops the statistical basis for the general principles of this wide range of interpretive tools, and illustrates them with applications to a variety of examples. The author begins the second part of the book by introducing the ICALC Toolkit for Stata, and then provides a series of start-to-finish application examples to illustrate how to interpret interaction effects for a variety of different techniques of analysis, beginning with OLS regression. For all the application examples, the data set(s) and the Stata code to reproduce the results will be available in the book and on a website for the book. Students often struggle with the abstract nature of many advanced statistical texts, and this book solves this issue by having a clear set of workable examples with data and explanations.

The Sage Encyclopedia Of Social Science Research Methods

Author: Michael Lewis-Beck
Publisher: SAGE
ISBN: 9780761923633
Size: 40.46 MB
Format: PDF, ePub
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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.

Multivariate General Linear Models

Author: Richard F. Haase
Publisher: SAGE
ISBN: 1412972493
Size: 19.73 MB
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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.