Data Construction And Data Analysis For Survey Research

Based on the needs of business, marketing and social science students, this book provides an accessible and easy-to-follow guide to survey data analysis. The book avoids the more usual statistics-driven perspective. Rather, it provides an intuitive feel for handling survey data by emphasising that data analysis is more about understanding the research objectives, what kinds of data have been collected, how quantitative data were generated by the process of measurement, how to create a data matrix and how to transform raw data before thinking about appropriate statistical calculations. The author begins by considering what data are, the different kinds of data that surveys generate, and the tripartite format of all quantitative data. The processes of measurement and the errors that may arise are carefully explained. Coverage of the creation and analysis of a data matrix using SPSS is then provided. The author then reviews what kinds of statistical procedure are required for what kinds of data and for what purposes. The book concludes by giving a review of strategies for coping with all the kinds of practical problems that arise in survey research. Reader-friendly throughout, Data Analysis: A Guide to Market and Social Research provides numerous worked examples, end-of-chapter questions and points for further discussion to help reinforce concepts learnt. A data diskette containing the worked examples in SPSS is also provided in the back of the book. Also available is a companion website with extra features to accompany the text, please take a look by clicking below - http://www.palgrave.com/business/kent/index.asp

Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.

The nature of survey research - The survey process - Sampling procedures - Questionnaire construction - The data collection stage - Coding practices - Designing survey - The process of data analysis - Single-variable statistics - Statistical inference for means - Two-variable tables - Measures of association - Control tables - Correlation and regression - Writing survey reports - Evaluating surveys - The ethics of polls.

Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University

This volume presents strategies for locating survey data and provides a comprehensive guide to US social science data archives, describing several major data files. Although the data sets are American, the techniques are widely applicable.

Engaging and informative, this book provides students and researchers with a pragmatic, new perspective on the process of collecting survey data. By proposing a post-positivist, interviewee-centred approach, it improves the quality and impact of survey data by emphasising the interaction between interviewer and interviewee. Extending the conventional methodology with contributions from linguistics, anthropology, cognitive studies and ethnomethodology, Gobo and Mauceri analyse the answering process in structured interviews built around questionnaires. The following key areas are explored in detail: An historical overview of survey research The process of preparing the survey and designing data collection The methods of detecting bias and improving data quality The strategies for combining quantitative and qualitative approaches The survey within global and local contexts Incorporating the work of experts in interpersonal and intercultural relations, this book offers readers an intriguing critical perspective on survey research. Giampietro Gobo, Ph.D., is Professor of Methodology of Social Research and Evaluation Methods at the Department of Social and Political Studies - University of Milan. He has published over fifty articles in the areas of qualitative and quantitative methods. His books include Doing Ethnography (Sage 2008) and Qualitative Research Practice (Sage 2004, co-edited with C. Seale, J.F. Gubrium and D. Silverman). He is currently engaged in projects in the area of workplace studies. Sergio Mauceri, Ph.D., is Lecturer in Methodology of Social Sciences and teaches Quantitative and Qualitative Strategies of Social Research at the Department of Communication and Social Research - University of Rome ‘La Sapienza’. He has published several books and articles on data quality in survey research, mixed strategies, ethnic prejudice, multicultural cohabitation, delay in the transition to adulthood, worker well-being in call centres and homophobia.

In this introduction to the different ways of analysing complex survey data, the authors consider new analytical approaches, review new software and introduce a model-based analysis that can be used for well-designed and relatively small-scale social surveys.