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Handbook of Data Analysis
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Handbook of Data Analysis

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April 2004 | 728 pages | SAGE Publications Ltd
This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond. Diagrams and tables are used effectively throughout the text and snippets of sample code provide useful additions to chapters for those of us who are less familiar with statistical software packages. Where equations are used to they are explained and documented with careful explanation of statistical notation. Each of the chapters in the book references a representative range of key authors and seminal texts, making it an ideal springboard for further and more advanced reading… the book provides an excellent reference of quantitative methodology and would provide a very useful addition to the shelves of researches and university libraries. - Environment and Planning

This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. However, the book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters.

A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.

`The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher' - Clive Seale, Brunel University

`With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. While quantitative methods are treated, from basic statistics through the general linear model and beyond, qualitative methods are by no means neglected. Indeed, a unique feature of this volume is the careful integration of quantitative and qualitative approaches. Undoubtedly, this integration succeeds because of the research strengths of the editors, leading social researchers who themselves employ both quantitative and qualitative methods' - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa and Editor of the SAGE `Quantitative Applications in the Social Sciences' series

`This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments' - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey

Melissa A Hardy and Alan Bryman
Introduction
Common Threads among Techniques of Data Analysis

 
 
PART ONE: FOUNDATIONS
Alan Bryman and Duncan Cramer
Constructing Variables
Melissa A Hardy
Summarizing Distributions
Lawrence Hazelrigg
Inference
Mortaza Jamshidian
Strategies for Analysis of Incomplete Data
Mary Maynard
Feminist Issues in Data Analysis
Dennis Smith
Historical Analysis
 
PART TWO: THE GENERAL LINEAR MODEL AND EXTENSIONS
Ross M Stolzenberg
Multiple Regression Analysis
Melissa A Hardy and John Reynolds
Incorporating Categorical Information into Regression Models
The Utility of Dummy Variables

 
James Jaccard and Tonya Dodge
Analyzing Contingent Effects in Regression Models
J Scott Long and Simon Cheng
Regression Models for Categorical Outcomes
Douglas L Anderton and Eric Cheney
Log Linear Analysis
 
PART THREE: LONGITUDINAL MODELS
Nancy Brandon Tuma
Modeling Change
Trond Petersen
Analyzing Panel Data
Fixed- and Random-Effects Models

 
Guang Guo and John Hipp
Longitudinal Analysis for Continuous Outcomes
Random Effects Models and Latent Trajectory Models

 
Paul Allison
Event History Analysis
Heather MacIndoe and Andrew Abbott
Sequence Analysis and Optimal Matching Techniques for Social Science Data
 
PART FOUR: NEW DEVELOPMENTS IN MODELING
Vincent Kang Fu, Christopher Winship and Robert D Mare
Sample Selection Bias Models
Jodie B Ullman and Peter M Bentler
Structural Equation Modeling
William Browne and J Rasbash
Multilevel Modeling
Christopher Winship and Michael Sobel
Causal Inference in Sociological Studies
Ronald L Breiger
The Analysis of Social Networks
 
PART FIVE: ANALYZING QUALITATIVE DATA
Raymond M Lee and Nigel G Fielding
Tools of Qualitative Data Analysis
Roberto P Franzosi
Content Analysis
Peter K Manning
Semiotics and Data Analysis
Steve E Clayman and Virginia Teas Gill
Conversation Analysis
Jonathan Potter
Discourse Analysis
Nick Pidgeon and Karen Henwood
Grounded Theory
Barbara Czarniawska
The Uses of Narrative in Social Science Research
Sara Delamont and Paul Atkinson
Qualitative Research and the Postmodern Turn

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ISBN: 9780761966524
£150.00

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