Methoden vergleichen
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| Doppelblindes vollständiges faktorielles Experiment× | Blockierter vollständiger faktorieller Versuchsplan× | |
|---|---|---|
| Fachgebiet | Versuchsplanung | Versuchsplanung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1935 (factorial foundations, Fisher); double-blind combined application from 1950s onward | 1935 (Fisher); systematized through 20th-century DOE literature |
| Urheber≠ | Full factorial design: Ronald A. Fisher; double-blind masking: formalized in clinical research mid-20th century | R. A. Fisher (blocking principle); full factorial DOE tradition |
| Typ≠ | Controlled experimental design with masking | Experimental design |
| Wegweisende Quelle | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 |
| Aliasnamen | double-masked full factorial design, double-blind complete factorial experiment, blinded full factorial RCT, double-blind factorial trial | blocked full factorial design, full factorial with blocking, complete factorial blocked design, BFF design |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | A double-blind full factorial experiment crosses every level of every independent variable to create all possible treatment combinations, while ensuring that neither participants nor outcome assessors know which condition each participant has been assigned to. This design simultaneously achieves comprehensive examination of main effects and all interactions, and protection against performance and detection bias through blinding — making it especially valuable in clinical, pharmacological, and behavioral research. | A blocked full factorial experiment tests every combination of all factor levels while grouping experimental runs into homogeneous blocks to isolate a known nuisance variable. This design preserves the power to detect all main effects and interactions of the factors of interest while preventing batch-to-batch, day-to-day, or machine-to-machine variability from inflating experimental error. |
| ScholarGateDatensatz ↗ |
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