Marginal Structural Models

By Michael Rosenblum. 2011

309 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology

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In Experimental and Cognitive Psychology

Citations in the corpus

Does Job Loss Shorten Life? (2009, methodology): “We will adopt a propensity score weighted estimator similar to the estimators proposed in Robins, Hernán, and Brumback (2000), and Hirano and Imbens (2001).”
Causal Inference for a Single Group of Causally-Connected Units Under Stratified Interference (2017, background): “While they were originally deﬁned for the purpose of estimating causal effects due to repeated exposures in the presence of time-varying confounding (Robins, 1998), their usage has since been expanded.”
Marginal and Nested Structural Models Using Instrumental Variables (2010, methodology): “We propose marginal and nested structural models using IVs under assumptions A1–A2 and refer to them as marginal and nested structural IV models, in the spirit of marginal and nested structural models of Robins (1998, 1999a) under the assumption of no unmeasured confounding, that is, Yd ⊥ D”
The effect of combined antiretroviral therapy on the overall mortality of HIV-infected individuals (2010, methodology): “Formally, under the assumption that all time-varying predictors of both cART and mortality were included in the analysis, our weighted model estimates the parameters of a marginal structural Cox model [19,36] and can be used to mimic a sequentially randomized trial in which patients were assigned to”
Effect of Physical Activity on Functional Performance and Knee Pain in Patients With Osteoarthritis: Analysis With Marginal Structural Models (2012, unknown): “Ankle pain 85 (13) 75 (12) 69 (11) 61 (10)”
Dynamic treatment regimes: technical challenges and applications (2014, methodology): “…of the conditional distributions of the outcomes Y1, Y2, Y , (for example, models for the Q-function) and then from these models infer the optimal DTR. Indirect estimation includes g-estimation in structural nested models (Robins, 1989, 1993, 1997) and its variations (Murphy, 2003; Robins, 2004).”
Standardization and Control for Confounding in Observational Studies: A Historical Perspective (2015, background): “As noted earlier, this was already derived by Westergaard (1882), although this was apparently not generally known.”
Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial. (2010, methodology): “Throughout, hazard ratios are used to measure the strength of association, 95% confidence limits are used to measure precision, robust variances (37–39) are used in conjunction with weighted Cox models (40), and confidence limit ratios are used to compare precision across estimates.”
Comparison of Approaches to Weight Truncation for Marginal Structural Cox Models (2013, background): “…structural models (MSMs), a class of models, that are used to model the marginal distribution of counterfactual variables, have been proposed to define the causal effect of a time-varying treatment in such challenging situations (Robins, 1997, 1999a,b; Robins et al., 2000; Robins and Hernán, 2008).”