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Joint Point Process Model for Counterfactual Treatment--Outcome Trajectories Under Policy Interventions
Çağlar Hızlı · ST John · Anne Juuti · Tuure Saarinen · Kirsi Pietiläinen · Pekka Marttinen

Policy makers need to predict the progression of an outcome before adopting a new treatment policy, which defines when and how a sequence of treatments affecting the outcome occurs in continuous time. Commonly, algorithms that predict interventional future outcome trajectories take a fixed sequence of future treatments as input. This excludes scenarios where the policy is unknown or a counterfactual analysis is needed. To handle these limitations, we develop a joint model for treatments and outcomes, which allows for the estimation of treatment policies and effects from sequential treatment--outcome data. It can answer interventional and counterfactual queries about interventions on treatment policies, as we show with a realistic semi-synthetic simulation study. This abstract is based on work that is currently under review (Anonymous).

Author Information

Çağlar Hızlı (Aalto University)
ST John (Aalto University)
Anne Juuti (University of Helsinki)
Tuure Saarinen (University of Helsinki)
Kirsi Pietiläinen (University of Helsinki)
Pekka Marttinen (Aalto University)

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