Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Geclusterd Gerandomiseerd Veldexperiment× | Factorieel Veldexperiment× | |
|---|---|---|
| Vakgebied | Experimenteel ontwerp | Experimenteel ontwerp |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | 1980s–1990s (formalized methodology) | 1920s–1935 (Fisher's foundational work); widely applied through 20th century |
| Grondlegger≠ | David M. Murray (group-randomized trials framework); applied broadly in public health and education research | Ronald A. Fisher (factorial principle); extended to field settings in agricultural and social sciences |
| Type≠ | Randomized experimental design | Experimental design |
| Oorspronkelijke bron≠ | Murray, D. M. (1998). Design and Analysis of Group-Randomized Trials. Oxford University Press. ISBN: 978-0195120424 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Aliassen | CRFE, cluster-randomized trial in the field, group-randomized field experiment, community-randomized field experiment | factorial design in the field, field factorial design, multi-factor field trial, factorial field trial |
| Verwant≠ | 4 | 5 |
| Samenvatting≠ | A cluster randomized field experiment (CRFE) assigns intact groups — schools, villages, clinics, workplaces — rather than individuals to treatment or control conditions, and the experiment is conducted in real-world settings rather than a laboratory. Randomization at the group level controls for contamination between conditions while preserving the ecological validity of the natural environment. It is the dominant design for evaluating community-level, school-based, or workplace interventions in public health, education policy, and development economics. | A factorial field experiment applies factorial experimental design — simultaneously manipulating two or more independent factors across all combinations of their levels — in a real-world field setting rather than a controlled laboratory. It allows researchers to estimate both main effects and interaction effects of multiple factors on an outcome under ecologically valid conditions, making findings directly relevant to practice. |
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