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Population Intervention Causal Effects Based on Stochastic Interventions

Muñoz, Iván Díaz ; van der Laan, Mark

Biometrics, 2012-06, Vol.68 (2), p.541-549 [Periódico revisado por pares]

Malden, USA: Blackwell Publishing Inc

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Título:
Population Intervention Causal Effects Based on Stochastic Interventions
Autor: Muñoz, Iván Díaz ; van der Laan, Mark
Assuntos: Aged ; BIOMETRIC METHODOLOGY ; Biometrics ; biometry ; Biometry - methods ; Causal effect ; Causality ; Computer Simulation ; Consistent estimators ; Counterfactual outcome ; Data Interpretation, Statistical ; Density estimation ; Double robustness ; equations ; Estimating techniques ; Estimation methods ; Estimators ; Exercise ; Health Promotion - statistics & numerical data ; Humans ; Inference ; Inverse problems ; issues and policy ; Likelihood Functions ; Maximum likelihood estimation ; Mortality ; Motor Activity ; physical activity ; Preliminary estimates ; probability ; Psychoeducational intervention ; Statistical variance ; Stochastic intervention ; Stochastic models ; Stochastic Processes ; Targeted maximum likelihood estimation
É parte de: Biometrics, 2012-06, Vol.68 (2), p.541-549
Notas: http://dx.doi.org/10.1111/j.1541-0420.2011.01685.x
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Descrição: Estimating the causal effect of an intervention on a population typically involves defining parameters in a nonparametric structural equation model (Pearl, 2000, Causality: Models, Reasoning, and Inference) in which the treatment or exposure is deterministically assigned in a static or dynamic way. We define a new causal parameter that takes into account the fact that intervention policies can result in stochastically assigned exposures. The statistical parameter that identifies the causal parameter of interest is established. Inverse probability of treatment weighting (IPTW), augmented IPTW (A‐IPTW), and targeted maximum likelihood estimators (TMLE) are developed. A simulation study is performed to demonstrate the properties of these estimators, which include the double robustness of the A‐IPTW and the TMLE. An application example using physical activity data is presented.
Editor: Malden, USA: Blackwell Publishing Inc
Idioma: Inglês;Francês

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Population Intervention Causal Effects Based on Stochastic Interventions

Muñoz, Iván Díaz ; van der Laan, Mark

Malden, USA: Blackwell Publishing Inc

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