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| Pilot Kontrolgruppe Eksperimentelt Design× | Kontrolgruppedesign× | |
|---|---|---|
| Fagområde | Forsøgsdesign | Forsøgsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | Mid-20th century; widely formalized by 1980s–2000s | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Ophavsperson≠ | Established through clinical and behavioral research traditions; formalized by Bradford Hill and colleagues in mid-20th century trial methodology | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Type≠ | Experimental design (pilot/feasibility variant) | Experimental research design |
| Oprindelig kilde≠ | Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., Robson, R., Thabane, M., Giangregorio, L., & Goldsmith, C. H. (2010). A tutorial on pilot studies: the what, why and how. BMC Medical Research Methodology, 10, 1. DOI ↗ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Aliasser | pilot controlled experiment, pilot RCT feasibility study, small-scale controlled trial, pilot control group study | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Relaterede | 4 | 4 |
| Resumé≠ | A pilot control group experimental design is a small-scale, preliminary experiment that includes both a treatment group and a control group, conducted before the main study to test whether the full trial is feasible. It produces early effect-size estimates, identifies protocol problems, and confirms that random (or systematic) assignment to conditions is workable — all while generating a genuine comparison between treated and untreated participants. | Control group experimental design is a fundamental experimental structure in which participants are assigned to at least two groups — a treatment group that receives the intervention and a control group that does not — so that the effect of the intervention can be isolated by comparing outcomes across groups. Randomisation of assignment strengthens causal inference by balancing known and unknown confounders. |
| ScholarGateDatasæt ↗ |
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