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Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Mchanganuo wa Mijadala ya Wakati wa Sera Iliyoingiliwa×Uchanganuzi wa Mfululizo wa Wakati Uliokatizwa (ITS)×
NyanjaUhitimisho wa KisababishiUhitimisho wa Kisababishi
FamiliaRegression modelRegression model
Mwaka wa asili1975 (intervention analysis); 2000s–2010s (policy evaluation framing)2002
MwanzilishiBox & Tiao (1975); popularised for policy by Shadish, Cook & Campbell (2002) and Bernal et al. (2017)Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
AinaQuasi-experimental causal designQuasi-experimental segmented regression
Chanzo asiliaBernal, 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 ↗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 ↗
Majina mbadalaITS for policy evaluation, policy ITS, segmented regression for policy, policy impact ITSITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Zinazohusiana45
MuhtasariInterrupted Time Series (ITS) for policy evaluation uses routinely collected aggregate time-series data to estimate the causal impact of a policy change. A segmented regression model splits the series at a known intervention date, estimating both an immediate level shift and a change in trend attributable to the policy — without requiring a randomised control group.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.
ScholarGateSeti ya data
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED
  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Policy Evaluation Interrupted Time Series · Interrupted Time Series. Imepatikana 2026-06-19 kutoka https://scholargate.app/sw/compare