Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Experimento de laboratorio doble ciego× | Experimento de laboratorio bloqueado× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | Mid-20th century (widespread adoption ~1950s onward) | 1926–1935 |
| Autor original≠ | Rooted in 19th-century pharmacological and psychological research traditions; systematized in clinical and experimental science through the 20th century | Ronald A. Fisher |
| Tipo≠ | Controlled experimental design with blinding | Controlled experimental design with blocking |
| Fuente seminal≠ | Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Alias | double-blind lab experiment, double-masked laboratory experiment, DB lab experiment, double-blind controlled lab study | blocked lab experiment, laboratory randomized block design, RBD laboratory study, blocked within-lab experiment |
| Relacionados | 5 | 5 |
| Resumen≠ | A double-blind laboratory experiment is a controlled experimental design conducted in a laboratory setting in which neither the participants nor the researchers directly administering the treatment know which condition each participant has been assigned to. This dual blinding, combined with the high degree of environmental control characteristic of laboratory settings, minimizes both participant expectancy effects and experimenter bias, making it one of the most rigorous designs available for isolating causal relationships between independent and dependent variables. | A blocked laboratory experiment is a controlled laboratory study in which experimental units are grouped into homogeneous blocks before treatment assignment, and treatments are then randomly assigned within each block. Blocking removes the influence of a known nuisance variable — such as participant batch, equipment run, or testing day — from the error term, increasing the precision of treatment comparisons without expanding sample size. |
| ScholarGateConjunto de datos ↗ |
|
|