方法对比

	异质性处理效应间断时间序列 (HTE-ITS)	面板数据中断时间序列
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	2000s–2010s	2000s–2010s
提出者	Extensions of Shadish, Cook & Campbell (2002) ITS framework; HTE formulation developed by Lopez Bernal and colleagues	Shadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial)
类型	Quasi-experimental segmented regression with subgroup moderation	Quasi-experimental causal inference
开创性文献	Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.	Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.
别名	HTE-ITS, Subgroup ITS, Effect-modifier ITS, Segmented ITS with interaction	panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
相关	4	5
摘要	Heterogeneous Treatment Effect Interrupted Time Series extends the standard ITS design to detect whether an intervention's effect on a time series differs systematically across subgroups or in response to unit-level moderators. Where ordinary ITS yields a single level-change and slope-change estimate, HTE-ITS adds interaction terms for a moderating variable, revealing who benefits more or less from the intervention and by how much.	Panel Data Interrupted Time Series (panel ITS) is a quasi-experimental method that estimates the causal effect of an intervention using repeated observations from multiple units over time. By exploiting variation across both units and time periods, it provides stronger causal identification than single-unit ITS, detecting changes in the level and slope of the outcome trajectory immediately following a clearly dated intervention.