手法を比較

	シミュレーションベースのパワー分析（モンテカルロ・パワー）	一元配置分散分析
分野	統計学	統計学
系統	Hypothesis test	Hypothesis test
提唱年	2011	1925
提唱者	Arnold et al. (2011); Green & MacLeod (2016) for mixed-model extension	Ronald A. Fisher
種類	Simulation-based (Monte Carlo)	Parametric mean comparison
原典	Arnold, B.F. et al. (2011). Simulation Methods to Estimate Design Power: An Overview for Applied Research. BMC Medical Research Methodology, 11, 94.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
別名	Monte Carlo power analysis, Monte Carlo simulation power, MC power, Simülasyon Tabanlı Güç Analizi (Monte Carlo Power)	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
関連	6	4
概要	Simulation-based power analysis estimates the statistical power and required sample size of a study by repeating a full analysis pipeline thousands of times on artificially generated data. Because it relies on Monte Carlo simulation rather than closed-form equations, it is applicable to designs — mixed models, complex measurement structures, non-standard outcomes — where analytical power formulas do not exist. The approach was systematically described for applied research by Arnold et al. in 2011, and the mixed-model implementation via the SIMR package was formalised by Green and MacLeod in 2016.	One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.