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Dynamic Interrupted Time Series

Dynamic Interrupted Time Series (Dynamic ITS) extends the standard ITS design by allowing intervention effects to build up, decay, or shift over multiple time lags rather than assuming a single instantaneous level change. It estimates how an intervention's impact evolves across time periods, making it especially suited to public health, health services research, and policy evaluation where effects accumulate gradually or wear off after initial impact.

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Dynamic Interrupted Time Series Analysis

Rekod kaedah taksonomik · regression-model / causal-inference

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