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Time Series Analysis


Time series and longitudinal modeling can be accomplished using a variety of modeling techniques.

Discontinuity Design and Analysis

Regression discontinuity design (RDD) is a quasi-experimental pretest-posttest design that elicits the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. By comparing observations lying closely on either side of the threshold, it is possible to estimate the local Average treatment effect in environments in which randomization was unfeasible.

Auto Regressive Integrated Moving-Average (ARIMA) Interrupted time series analysis

One special kind of ARIMA model with input series is called an intervention model or interrupted time series model. In an intervention model, the input series is an indicator variable containing discrete values that flag the occurrence of an event affecting the response series. This event is an intervention in or an interruption of the normal evolution of the response time series, which, in the absence of the intervention, is usually assumed to be a pure ARIMA process.

Intervention models can be used both to model and forecast the response series and to analyze the impact of the intervention. When the focus is on estimating the effect of the intervention, the process is often called intervention analysis or interrupted time series analysis.

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