পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| হেটেরোজিনিয়াস ট্রিটমেন্ট এফেক্ট ইন্টারাপ্টেড টাইম সিরিজ (HTE-ITS)× | প্যানেল ডেটা ইন্টারাপ্টেড টাইম সিরিজ× | |
|---|---|---|
| ক্ষেত্র | কার্যকারণ অনুমান | কার্যকারণ অনুমান |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর | 2000s–2010s | 2000s–2010s |
| প্রবর্তক≠ | 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) |
| ধরন≠ | Quasi-experimental segmented regression with subgroup moderation | Quasi-experimental causal inference |
| মৌলিক উৎস | 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. DOI ↗ | 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. DOI ↗ |
| অপর নাম | HTE-ITS, Subgroup ITS, Effect-modifier ITS, Segmented ITS with interaction | panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series |
| সম্পর্কিত≠ | 4 | 5 |
| সারসংক্ষেপ≠ | 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. |
| ScholarGateডেটাসেট ↗ |
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