Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Factorial Survey Experiment× | Survey Experiment× | |
|---|---|---|
| Campo | Political Science | Political Science |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1982 | 2011 |
| Autor original≠ | Peter H. Rossi and collaborators | Experimental political science; synthesized by Diana Mutz |
| Tipo≠ | Multi-factor randomized vignette experiment | Randomized experiment embedded in a survey |
| Fuente seminal≠ | Wallander, L. (2009). 25 Years of Factorial Surveys in Sociology: A Review. Social Science Research, 38(3), 505–520. DOI ↗ | Mutz, D. C. (2011). Population-Based Survey Experiments. Princeton, NJ: Princeton University Press. ISBN: 9780691144528 |
| Alias | Factorial survey, Factorial survey approach, Multi-factor vignette survey, Rossi vignette method | Population-based survey experiment, Survey-embedded experiment, Question-wording experiment, Framing experiment |
| Relacionados≠ | 3 | 4 |
| Resumen≠ | A factorial survey experiment, often simply called a factorial survey, asks respondents to judge short descriptions — vignettes — whose multiple features are fully crossed and randomly varied. By factorially combining many dimensions, each at several levels, the design generates a large universe of vignettes; respondents rate a random sample of them, and regression of the ratings on the dimension levels recovers the independent causal effect of each feature on judgment. It scales the single-scenario vignette experiment up to many simultaneously manipulated attributes. | 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. |
| ScholarGateConjunto de datos ↗ |
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