Сравнение методов

	Факториальный естественный эксперимент	Факторный эксперимент
Область	Планирование эксперимента	Планирование эксперимента
Семейство	Process / pipeline	Process / pipeline
Год появления	1920s (factorial origins, Fisher); natural experiment formalization 1990s–2000s; factorial natural experiment usage widespread 2000s–present	1926–1935
Автор метода	Extension of natural experiment tradition (Dunning, Angrist & Pischke) combined with factorial design logic (Fisher)	Ronald A. Fisher
Тип	Quasi-experimental research design	Quantitative experimental design
Основополагающий источник	Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Другие названия	factorial quasi-experiment, multi-factor natural experiment, factorial exogenous variation design	factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design
Связанные	4	6
Сводка	A factorial natural experiment exploits naturally occurring exogenous variation across two or more factors simultaneously, allowing researchers to estimate main effects and interactions without random assignment. Natural events, policy changes, or institutional rules create treatment conditions that approximate a factorial structure, enabling causal inference in observational settings where controlled experimentation is infeasible or unethical.	A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect.