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Difference-in-Means Estimator×Survey Experiment×
ValdkondPolitical SciencePolitical Science
PerekondProcess / pipelineProcess / pipeline
Tekkeaasta19232011
LoojaJerzy Neyman (design-based potential-outcomes framework)Experimental political science; synthesized by Diana Mutz
TüüpDesign-based estimator of the average treatment effectRandomized experiment embedded in a survey
AlgallikasGerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis, and Interpretation. New York: W. W. Norton. ISBN: 9780393979954Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528
RööpnimetusedNeyman estimator, Design-based ATE estimator, Difference of sample means, Mean-difference treatment effect estimatorPopulation-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment
Seotud44
KokkuvõteThe difference-in-means estimator is the design-based workhorse for analyzing randomized experiments: it estimates the average treatment effect simply as the difference between the average outcome among treated units and the average outcome among control units. Rooted in Jerzy Neyman's potential-outcomes framework and central to modern treatments by Imbens and Rubin and by Gerber and Green, it is unbiased under randomization, comes with a conservative Neyman variance estimator, and supports exact randomization inference, requiring no model of how outcomes are generated.A survey experiment embeds a randomized experiment inside a survey: respondents are randomly assigned to different versions of a question, frame, or stimulus, and their answers are compared to estimate a causal effect. By combining the internal validity of randomization with the representative samples and rich measurement of survey research, survey experiments — especially population-based ones — let political scientists draw causal inferences about how information, framing, or message attributes shape public attitudes and behavior.
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ScholarGateVõrdle meetodeid: Difference-in-Means Estimator · Survey Experiment. Loetud 2026-06-24 aadressilt https://scholargate.app/et/compare