قارن الطرق

	تجربة عاملية كاملة تكيفية	التجربة التكيفية
المجال	التصميم التجريبي	التصميم التجريبي
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	1950s (factorial foundations); adaptive extensions prominent from 1990s onward	1940s–1970s (sequential foundations); formalised in clinical and behavioural research by 1980s–2000s
صاحب الطريقة	Rooted in Box & Hunter factorial design tradition; adaptive extensions formalised by Atkinson, Donev and others in optimal design theory	Abraham Wald (sequential analysis foundation); expanded by Robbins, Armitage, and others
النوع	Experimental design	Experimental research design
المصدر التأسيسي	Atkinson, A., Donev, A., & Tobias, R. (2007). Optimum Experimental Designs, with SAS. Oxford University Press. ISBN: 978-0199296606	Chow, S. C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886761
الأسماء البديلة	adaptive full-factorial design, sequential full factorial experiment, adaptive complete factorial design, dynamic full factorial trial	adaptive design, response-adaptive randomization, adaptive trial, adaptive randomization
ذات صلة	5	5
الملخص	An adaptive full factorial experiment is an experimental design that starts with a complete crossing of all factors and all their levels, then uses interim data to modify subsequent runs — dropping unpromising factor levels, adding new ones, or re-allocating replication — while preserving the full factorial structure within each phase. This integration of full factorial coverage with adaptive decision rules allows researchers to explore all main effects and interactions without committing to a fixed, inefficient run plan before any data are observed.	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.