Handbook of Data Analysis

'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' - "Environment and Planning". '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 ' - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa. '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.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. 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.

ISBN 1848601166   Pages 728 ISBN13 9781848601161 (What's this?)   Volumes 1 Publisher SAGE Publications Ltd   Weight (grammes) 1238 Imprint SAGE Publications Ltd   Published in London Format Paperback   Height (mm) 246 Publication date 31 May 2009   Width (mm) 174 DEWEY 300.15195   Spine width (mm) 38 DEWEY edition DC22   Academic level Postgraduate

1		Introduction: Common Threads among Techniques of Data Analysis by Melissa Hardy and Alan Bryman		1
Pt. I		Foundations		15
2		Constructing Variables by Alan Bryman and Duncan Cramer		17
3		Summarizing Distributions by Melissa Hardy		35
4		Inference by Lawrence Hazelrigg		65
5		Strategies for Analysis of Incomplete Data by Mortaza Jamshidian		113
6		Feminist Issues in Data Analysis by Mary Maynard		131
7		Historical Analysis by Dennis Smith		147
Pt. II		The General Linear Model and Extensions		163
8		Multiple Regression Analysis by Ross M. Stolzenberg		165
9		Incorporating Categorical Information into Regression Models: The Utility of Dummy Variables 209 by Melissa Hardy and John Reynolds
10		Analyzing Contingent Effects in Regression Models by James Jaccard and Tonya Dodge		237
11		Regression Models for Categorical Outcomes by J. Scott Long and Simon Cheng		259
12		Log-Linear Analysis by Douglas L. Anderton and Eric Cheney		285
Pt. III		Longitudinal Models		307
13		Modeling Change by Nancy Brandon Tuma		309
14		Analyzing Panel Data: Fixed- and Random-Effects Models by Trond Petersen		331
15		Longitudinal Analysis for Continuous Outcomes: Random Effects Models and Latent Trajectory Models by Guang Guo and John Hipp		347
16		Event History Analysis by Paul Allison		369
17		Sequence Analysis and Optimal Matching Techniques for Social Science Data by Heather MacIndoe and Andrew Abbott		387
Pt. IV		New Developments in Modeling		407
		More...

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