Marginal structural model

Known as: Marginal structural models 
Marginal structural models are a class of statistical models used for causal inference in epidemiology. Such models handle the issue of time… (More)
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Topic mentions per year

Topic mentions per year

1999-2016
024619992016

Papers overview

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Review
2016
Review
2016
Much of epidemiology and clinical medicine is focused on the estimation of treatments or interventions administered over time. In… (More)
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2014
2014
Saarela et al. are concerned with integrating propensity scores into a Bayesian framework. Some of us have previously written… (More)
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2013
2013
Marginal structural models (MSMs) are becoming increasingly popular as a tool to make causal inference from longitudinal data… (More)
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2010
2010
One of the main objectives in clinical epidemiology is to detect a relation between treatment and outcome. We address data where… (More)
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2010
2010
The cross-validation deletion-substitution-addition (cvDSA) algorithm is based on data-adaptive estimation methodology to select… (More)
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2010
2010
Sufficient cause interactions concern cases in which there is a particular causal mechanism for some outcome that requires the… (More)
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2009
2009
Marginal structural models were introduced in order to provide estimates of causal effects from interventions based on… (More)
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2008
2008
The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection… (More)
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2005
2005
Longitudinal studies in which exposures, confounders, and outcomes are measured repeatedly over time have the potential to allow… (More)
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Highly Cited
1999
Highly Cited
1999
Robins (1993, 1994, 1997, 1998ab) has developed a set of causal or counterfactual models, the structural nested models (SNMs… (More)
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