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Factorial Survey Experiments
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Factorial Survey Experiments

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December 2014 | 168 pages | SAGE Publications, Inc

Filling a gap in the literature of the field, this first-of-its-kind book provides researchers with a practical guide to using the factorial survey method to assess respondents’ beliefs about the world, judgment principles, or decision rules through multi-dimensional stimuli (“vignettes”) that resemble real-life decision-making situations. Using insightful examples to illustrate their arguments, the authors guide researchers through all relevant steps, including how to set up the factorial experimental design (drawing samples of vignettes and respondents), how to handle the practical challenges that must be mastered when an experimental plan with many different treatments is embedded in a survey format, and how to deal with questions of data analysis. In addition to providing the “how-tos” of designing factorial survey experiments, the authors cover recent developments of similar methods, such as conjoint analyses, choice experiments, and more advanced statistical tools.


 
1. Introduction
 
2. Why and When to Use Factorial Survey Methods
 
3. Setting Up the Experimental Design
 
4. Setting Up the Survey
 
5. Data Analyses
 
6. Further Aspects
 
7. Concluding Remarks

Supplements

Student Study Site
Our companion website for ?Factorial Survey Experiments? at study.sagepub.com/auspurg_hinz is completely open-access and offers data files, exercises, and a glossary of key terms.
Key features

KEY FEATURES:

 

  • This volume is the first book-length discussion of factorial survey research, a method that allows researchers to combine the advantages of experimental designs and surveys.
  • This hands-on guide introduces readers to the key methodological features, applications, and techniques of setting up a factorial survey and analyzing the data from it.
  • Readers learn how to select dimensions and vignette texts, how to use the vignettes in the questionnaires, how to select answer scales and modes of presentation, and how to manage data.
  • Methodological challenges are discussed, including important internal and external limitations and validity issues, as well as recommendations for robustness and validation checks.
  • Each section concludes with a brief summary that helps readers master important issues.
  • Throughout the book, a comprehensive application with complete real data files helps to explain the experimental set-up, as well as all the steps in data management and data analysis.
  • An accompanying website includes additional learning material, such as statistical syntax files and glossaries on technical terms.

Sample Materials & Chapters

Table of Contents

Chapter 1


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