手法を比較

	適応的ABAデザイン	シングル被験者実験計画
分野	実験計画法	実験計画法
系統	Process / pipeline	Process / pipeline
提唱年	1968 (ABA foundation); adaptive extensions formalized ~2010–2020	1960s (Sidman 1960; formal applied codification by Kazdin and Baer in 1970s–1980s)
提唱者	Baer, Wolf & Risley (ABA baseline); adaptive decision-rule extensions developed in single-case methodology literature (Kratochwill & Levin, 2010s)	Murray Sidman (foundational tactics); B. F. Skinner (applied behavior analysis lineage)
種類	Single-subject experimental design with adaptive phase rules	Experimental research design
原典	Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1(1), 91–97.	Kazdin, A. E. (1982). Single-Case Research Designs: Methods for Clinical and Applied Settings. Oxford University Press. ISBN: 978-0195030440
別名	adaptive withdrawal design, adaptive ABA withdrawal design, data-driven ABA design, adaptive single-case ABA	SSED, single-case experimental design, n-of-1 design, intrasubject replication design
関連	6	6
概要	The Adaptive ABA Design is a single-subject experimental framework that follows the classic three-phase ABA withdrawal structure — baseline (A1), intervention (B), and return-to-baseline (A2) — while embedding prospective decision rules that allow researchers or clinicians to extend, shorten, or otherwise modify each phase in response to observed data patterns rather than following a fixed schedule. This adaptive layer makes the design responsive to individual participant trajectories while preserving experimental control.	Single-subject experimental design (SSED) establishes experimental control by repeatedly measuring one individual (or a small number of individuals) across baseline and intervention phases, using the participant as their own control. Instead of comparing groups, it compares the participant's own behavior across conditions over time. Widely used in applied behavior analysis, special education, rehabilitation, and clinical psychology, SSED allows causal inference from small or unique samples where group designs are impractical.