Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño Experimental Adaptativo× | Metodología de Superficie de Respuesta (RSM)× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia≠ | Process / pipeline | Hypothesis test |
| Año de origen≠ | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s | 1951 |
| Autor original≠ | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others | George E. P. Box & K. B. Wilson |
| Tipo≠ | Experimental research design | Second-order polynomial response surface model |
| Fuente seminal≠ | Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761 | Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45. link ↗ |
| Alias≠ | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization | RSM, Central Composite Design, Box-Behnken Design, CCD |
| Relacionados≠ | 5 | 7 |
| Resumen≠ | An adaptive experiment is an experimental design in which pre-specified rules allow the protocol to be modified — such as reallocating participants to better-performing arms, stopping early for efficacy or futility, or changing sample size — based on accumulating interim data, while maintaining statistical validity. Adaptive designs are widely used in clinical trials, behavioural economics, and online platform testing to improve efficiency and ethics without sacrificing inferential rigour. | Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics. |
| ScholarGateConjunto de datos ↗ |
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