The Generalizability of Survey Experiments

TLDR

Survey experiments combine causal inference with population-based sampling, yet most studies use convenience samples, sparking debate over their external validity. The authors compare treatment effects from convenience samples to those from population samples in two studies. Study 1 contrasts four convenience sample types with a population sample, while Study 2 examines 20 experiments run on a population sample and MTurk. Results show substantial similarity between convenience and representative samples, supporting their use but offering guidance for future research.

Abstract

Abstract Survey experiments have become a central methodology across the social sciences. Researchers can combine experiments’ causal power with the generalizability of population-based samples. Yet, due to the expense of population-based samples, much research relies on convenience samples (e.g. students, online opt-in samples). The emergence of affordable, but non-representative online samples has reinvigorated debates about the external validity of experiments. We conduct two studies of how experimental treatment effects obtained from convenience samples compare to effects produced by population samples. In Study 1, we compare effect estimates from four different types of convenience samples and a population-based sample. In Study 2, we analyze treatment effects obtained from 20 experiments implemented on a population-based sample and Amazon's Mechanical Turk (MTurk). The results reveal considerable similarity between many treatment effects obtained from convenience and nationally representative population-based samples. While the results thus bolster confidence in the utility of convenience samples, we conclude with guidance for the use of a multitude of samples for advancing scientific knowledge.