Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Endorsement Experiment× | Survey Experiment× | |
|---|---|---|
| Галузь | Political Science | Political Science |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи | 2011 | 2011 |
| Автор методу≠ | Bullock, Imai & Shapiro (statistical framework) | Experimental political science; synthesized by Diana Mutz |
| Тип≠ | Indirect survey experiment for sensitive latent support | Randomized experiment embedded in a survey |
| Основоположне джерело≠ | Bullock, W., Imai, K., & Shapiro, J. N. (2011). Statistical Analysis of Endorsement Experiments: Measuring Support for Militant Groups in Pakistan. Political Analysis, 19(4), 363–384. DOI ↗ | Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528 |
| Інші назви | Endorsement question design, Endorsement experiment design, Indirect support measurement, Group-endorsement experiment | Population-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment |
| Пов'язані | 4 | 4 |
| Підсумок≠ | An endorsement experiment indirectly measures latent support for a sensitive or stigmatized actor by randomizing whether a policy is attributed to that actor and comparing how respondents' support for the policy shifts. Formalized statistically by Bullock, Imai, and Shapiro in 2011 to measure support for militant groups in Pakistan, the design infers favorability toward an actor that respondents would not safely disclose directly from the change in policy support it induces, typically estimated with hierarchical item-response models. | 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. |
| ScholarGateНабір даних ↗ |
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