Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Esperimento sul campo in doppio cieco× | Esperimento sul Campo× | |
|---|---|---|
| Campo | Disegno sperimentale | Disegno sperimentale |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1960s onward (field experiment tradition); double-blind controls applied from 1970s in social and policy field trials | 1920s–1930s (agriculture); 1990s–2000s (social sciences) |
| Ideatore≠ | Fisher, R. A. (randomized field trials); double-blind practice traced to 19th-century clinical research, formalized for field settings by Campbell & Stanley (1963) | Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004) |
| Tipo | Experimental design | Experimental design |
| Fonte seminale≠ | Gerber, A. S., & Green, D. P. (2012). Field Experiments: Design, Analysis, and Interpretation. W. W. Norton. ISBN: 978-0393979954 | Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. DOI ↗ |
| Alias | double-masked field trial, double-blind naturalistic experiment, blinded field study, DB field experiment | field trial, natural field experiment, randomized field experiment, field RCT |
| Correlati | 5 | 5 |
| Sintesi≠ | A double-blind field experiment combines the high external validity of a real-world field setting with double-blind masking, in which neither the participants nor the personnel delivering the treatment know who has been assigned to the treatment or control condition. This design controls simultaneously for participant expectation effects and for experimenter/enumerator demand effects, making it one of the most rigorous tools available for causal inference outside the laboratory. | A field experiment applies the logic of a randomized controlled trial in a naturally occurring, real-world environment rather than an artificial laboratory. Participants are randomly assigned to treatment and control conditions while going about everyday activities, allowing researchers to estimate causal effects with high internal validity while preserving a level of ecological realism that laboratory settings cannot offer. The design is especially prominent in economics, public health, political science, and development research. |
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