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| Bayesovská regresia× | Analýza prerušovaných časových radov (ITS)× | |
|---|---|---|
| Odbor≠ | Bayesovské metódy | Kauzálna inferencia |
| Rodina≠ | Bayesian methods | Regression model |
| Rok vzniku≠ | — | 2002 |
| Tvorca≠ | — | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| Typ≠ | Bayesian linear model | Quasi-experimental segmented regression |
| Pôvodný zdroj≠ | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 | Bernal, J. L., 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 ↗ |
| Ďalšie názvy | bayesian linear regression, probabilistic regression, bayesian regresyon | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| Príbuzné≠ | 2 | 5 |
| Zhrnutie≠ | Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off. | Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope. |
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