title: Twice-weighted multiple interval estimation of a marginal structural model to analyze cost-effectiveness.
abstract: Cost-effectiveness analysis is an important tool that can be applied to the evaluation of a health treatment or policy. When the observed costs and outcomes result from a nonrandomized treatment, making causal inference about the effects of the treatment requires special care. The challenges are compounded when the observation period is truncated for some of the study subjects. This paper presents a method of unbiased estimation of cost-effectiveness using observational study data that is not fully observed. The method-twice-weighted multiple interval estimation of a marginal structural model-was developed in order to analyze the cost-effectiveness of treatment protocols for advanced dementia residents living nursing homes when they become acutely ill. A key feature of this estimation approach is that it facilitates a sensitivity analysis that identifies the potential effects of unmeasured confounding on the conclusions concerning cost-effectiveness.
authors.affiliation: Department of Population Health, NYU School of Medicine, New York, NY, U.S.A.
authors.forename: K S
authors.initials: KS
authors.lastname: Goldfeld
mesh_terms: D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D003704:Dementia / Q000191:economics*; D006801:Humans; D015233:Models, Statistical; D009735:Nursing Homes / Q000191:economics*; D064887:Observational Studies as Topic / Q000379:methods*
keywords: advanced dementia; causal inference; censoring; cost-effectiveness; marginal structural model; observational data; sensitivity analysis