Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Experimentare adaptivă× | Metodologia Suprafeței de Răspuns (RSM)× | |
|---|---|---|
| Domeniu | Design experimental | Design experimental |
| Familie≠ | Process / pipeline | Hypothesis test |
| Anul apariției≠ | 1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s | 1951 |
| Autorul original≠ | Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others | George E. P. Box & K. B. Wilson |
| Tip≠ | Experimental research design | Second-order polynomial response surface model |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative≠ | adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization | RSM, Central Composite Design, Box-Behnken Design, CCD |
| Înrudite≠ | 5 | 7 |
| Rezumat≠ | 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. |
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