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| Ein Einzelblind-Laborversuch× | Experimentelles Design mit Kontrollgruppe× | |
|---|---|---|
| Fachgebiet | Versuchsplanung | Versuchsplanung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | Late 19th century; codified in 20th-century clinical and behavioral research | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Urheber≠ | Formalized in experimental psychology and pharmacology; Peirce & Jastrow (1884) early instance | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Typ≠ | Controlled experimental design | Experimental research design |
| Wegweisende Quelle≠ | Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560 | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Aliasnamen≠ | single-masked laboratory study, participant-blind lab experiment, single-blind controlled lab study | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | A single-blind laboratory experiment is a controlled study conducted in a laboratory setting in which participants do not know which condition (e.g., treatment or control) they have been assigned to, while the researchers administering the conditions are aware. This masking of participants reduces demand characteristics and response bias without requiring full investigator blinding, and the controlled laboratory environment allows tight manipulation of independent variables and precise measurement of outcomes. | 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. |
| ScholarGateDatensatz ↗ |
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