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Title: Exploration of marginal structural models for survival outcomes
Author: Havercroft, William G.
ISNI:       0000 0004 5922 3882
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2014
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A marginal structural model parameterises the distribution of an outcome given a treatment intervention, where such a distribution is the fundamental probabilistic representation of the causal effect of treatment on the outcome. Causal inference methods are designed to consistently estimate aspects of these causal distributions, in the presence of interference from non-causal associations which typically occur in observational data. One such method, which involves the application of inverse probability of treatment weights, directly targets the parameters of marginal structural models. The asymptotic properties and practical applicability of this method are well established, but little attention has been paid to its finite-sample performance. This is because simulating data from known distributions which are entirely suitable for such investigations generally presents a significant challenge, especially in scenarios where the outcome is survival time. We illuminate these issues, and propose and implement certain solutions, considering separately the cases of static (pre-determined) and dynamic (tailored) treatment interventions. In so doing, we explore both theoretical and practical aspects of marginal structural models for survival outcomes, and the associated inference method.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available