
- 728 pages
- English
- PDF
- Available on iOS & Android
Handbook of Data Analysis
About this book
?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.
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Information
Table of contents
- COVER
- Contents
- Preface
- Notes on Contributors
- 1 Introduction: Common Threads among Techniques of Data Analysis
- PART I - Foundations
- 2 Constructing Variables
- 3 Summarizing Distributions
- 4 Inference
- 5 Strategies for Analysis of Incomplete Data
- 6 Feminist Issues in Data Analysis
- 7 Historical Analysis
- PART II - The General Linear Model and Extensions
- 8 Multiple Regression Analysis
- 9 Incorporating Categorical Information into Regression Models:The Utility of Dummy Variables
- 10 Analyzing Contingent Effects in Regression Models
- 11 Regression Models for Categorical Outcomes
- 12 Log-Linear Analysis
- PART III - Longitudinal Models
- 13 Modeling Change
- 14 Analyzing Panel Data: Fixed- and Random-Effects Models
- 15 Longitudinal Analysis for Continuous Outcomes:Random Effects Models and Latent Trajectory Models
- 16 Event History Analysis
- 17 Sequence Analysis and Optimal Matching Techniques for Social Science Data
- PART IV - New Developments in Modeling
- 18 Sample Selection Bias Models
- 19 Structural Equation Modeling
- 20 Multilevel Modelling
- 21 Causal Inference in Sociological Studies
- 22 The Analysis of Social Networks
- PART V - Analyzing Qualitative Data
- 23 Tools for Qualitative Data Analysis
- 24 Content Analysis
- 25 Semiotics and Data Analysis
- 26 Conversation Analysis
- 27 Discourse Analysis
- 28 Grounded Theory
- 29 The Uses of Narrative in Social Science Research
- 30 Qualitative Research and the Postmodern Turn
- Appendix
- iNDEX