Population-Based Survey Experiments

Population-Based Survey Experiments

Population-Based Survey Experiments

Population-Based Survey Experiments

Synopsis

Population-based survey experiments have become an invaluable tool for social scientists struggling to generalize laboratory-based results, and for survey researchers besieged by uncertainties about causality. Thanks to technological advances in recent years, experiments can now be administered to random samples of the population to which a theory applies. Yet until now, there was no self-contained resource for social scientists seeking a concise and accessible overview of this methodology, its strengths and weaknesses, and the unique challenges it poses for implementation and analysis.


Drawing on examples from across the social sciences, this book covers everything you need to know to plan, implement, and analyze the results of population-based survey experiments. But it is more than just a "how to" manual. This lively book challenges conventional wisdom about internal and external validity, showing why strong causal claims need not come at the expense of external validity, and how it is now possible to execute experiments remotely using large-scale population samples.


Designed for social scientists across the disciplines, Population-Based Survey Experiments provides the first complete introduction to this methodology.



  • Offers the most comprehensive treatment of the subject

  • Features a wealth of examples and practical advice

  • Reexamines issues of internal and external validity

  • Can be used in conjunction with downloadable data from Experiment Central.org for design and analysis exercises in the classroom

Excerpt

This book is intended to fill a gap in the literature on research methods in the social sciences. To date, methods textbooks have yet to formally incorporate population-based survey experiments into the repertoire of approaches that are taught to social scientists in training. Though this is likely to change in the not-too-distant future, for now my hope is that this volume will serve that purpose. Population-based survey experiments are not only useful as a tool for better understanding the social world; they also provide insight into the strengths and weaknesses of existing methods.

I owe my own enthusiasm and interest in population-based experiments to many different driving forces, but probably the first cause was Paul Sniderman. I had the good fortune to meet Paul during graduate school, but only came to know him well many years later in my career. In addition to championing this methodological approach, Paul served as a mentor to my career as well as the careers of many other scholars. He also planted the idea that I need not rely on secondary data for purposes of testing my research ideas, and thus encouraged me to pursue original data collection opportunities as frequently as possible.

After I participated in the early Multi-Investigator Study, it was Paul’s idea to introduce me to Skip Lupia to talk about serving as co-Principal Investigators of future multi-investigator studies. This could not have been a better idea, because Skip could not have been a more generous collaborator. Undoubtedly, this was one of the smoothest and most enjoyable working relationships I have had. Together, during a year we shared at the Center for Advanced Study in the Behavioral Sciences, we hatched the idea for the proposal to the National Science Foundation for Time-sharing Experiments for the Social Sciences (TESS). After receiving the grant, we divided up the labor and plunged ahead, not quite knowing what to expect from the social science community.

The response was nothing short of wonderful, which is why I sincerely thank the National Science Foundation for the generous funding that brought TESS into being, and for their continued sponsorship. Although it probably distracted me from my own research agenda for quite a few years, the breadth of exposure that TESS gave me to other social science fields—at least a passing familiarity with fields far beyond my own—made it more than worthwhile. In addition, by observing how others made use of population-based survey experiments, my own work became stronger and more methodologically innovative. Further, my role in TESS afforded me . . .

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