Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Naturlig eksperiment× | Felteksperiment – Randomisert eksperiment i virkelige omgivelser× | |
|---|---|---|
| Fagfelt | Forsøksdesign | Forsøksdesign |
| Familie | Process / pipeline | Process / pipeline |
| Opprinnelsesår≠ | 1990s (formal methodological articulation); earlier in epidemiology (John Snow, 1854) | 1920s–1930s (agriculture); 1990s–2000s (social sciences) |
| Opphavsperson≠ | Varied; systematized in econometrics and political science (e.g., Meyer 1995; Angrist & Krueger 1991) | Formalized by R. A. Fisher (1935); systematized in social sciences by Harrison & List (2004) |
| Type≠ | Quasi-experimental research design | Experimental design |
| Opprinnelig kilde≠ | Meyer, B. D. (1995). Natural and quasi-experiments in economics. Journal of Business and Economic Statistics, 13(2), 151–161. DOI ↗ | Harrison, G. W., & List, J. A. (2004). Field experiments. Journal of Economic Literature, 42(4), 1009–1055. DOI ↗ |
| Alias | natural quasi-experiment, naturally occurring experiment, exogenous shock design, as-if randomization | field trial, natural field experiment, randomized field experiment, field RCT |
| Relaterte≠ | 3 | 5 |
| Sammendrag≠ | A natural experiment exploits a real-world event, policy, or circumstance that assigns individuals to treatment and control conditions in a way that is plausibly random — or at least exogenous to the outcome of interest. Because the researcher does not control assignment, it occupies a middle ground between a true randomized controlled trial and purely observational research, offering stronger causal leverage than conventional observational designs when the as-if randomization assumption holds. | 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. |
| ScholarGateDatasett ↗ |
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