Optimal probability weights for estimating causal effects of time-varying treatments with marginal structural Cox models.
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DOI: 10.1002/sim.8080
Abstract: Marginal structural Cox models have been used to estimate the causal effect of a time-varying treatment on a survival outcome in the presence of time-dependent confounders. These methods rely on the positivity assumption, which states… read more here.
Keywords: cox models; time varying; time; marginal structural ... See more keywords
Estimating controlled direct effects through marginal structural models
Sign Up to like & getrecommendations! Published in 2020 at "Political Science Research and Methods"
DOI: 10.1017/psrm.2020.3
Abstract: Abstract When working with panel data, many researchers wish to estimate the direct effects of time-varying factors on future outcomes. However, when a baseline treatment affects both the confounders of further stages of the treatment… read more here.
Keywords: estimating controlled; controlled direct; direct effects; structural models ... See more keywords
A simulation study on implementing marginal structural models in an observational study with switching medication based on a biomarker
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DOI: 10.1080/10543406.2017.1402783
Abstract: ABSTRACT Assessing treatment effectiveness in longitudinal data can be complex when treatments are not randomly assigned and patients are allowed to switch treatment to other or no treatment, often in a manner that is driven… read more here.
Keywords: based biomarker; treatment; study; marginal structural ... See more keywords
Dealing with Treatment-confounder Feedback and Sparse Follow-up in Longitudinal studies - Application of a Marginal Structural Model in a Multiple Sclerosis Cohort.
Sign Up to like & getrecommendations! Published in 2020 at "American journal of epidemiology"
DOI: 10.1093/aje/kwaa243
Abstract: The beta-interferons are widely prescribed platform therapies for patients with multiple sclerosis (MS). We accessed a cohort of patients with relapsing onset MS from British Columbia, Canada (1995-2013) to examine the potential survival advantage associated… read more here.
Keywords: structural model; treatment confounder; marginal structural; confounder feedback ... See more keywords
Marginal structural models for life-course theories and social epidemiology: Definitions, sources of bias, and simulated illustrations.
Sign Up to like & getrecommendations! Published in 2021 at "American journal of epidemiology"
DOI: 10.1093/aje/kwab253
Abstract: Social epidemiology aims to identify social structural risk factors thus informing targets and timing of interventions. Ascertaining which interventions will be most effective and when they should be implemented is challenging because social conditions vary… read more here.
Keywords: life course; marginal structural; epidemiology; social epidemiology ... See more keywords
Instrumental variable estimation of the marginal structural Cox model for time-varying treatments.
Sign Up to like & getrecommendations! Published in 2023 at "Biometrika"
DOI: 10.1093/biomet/asab062
Abstract: Robins (1998) introduced marginal structural models, a general class of counterfactual models for the joint effects of time-varying treatments in complex longitudinal studies subject to time-varying confounding. Robins (1998) established the identification of marginal structural… read more here.
Keywords: time; structural cox; instrumental variable; model ... See more keywords
Semiparametric Bayesian inference for optimal dynamic treatment regimes via dynamic marginal structural models.
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DOI: 10.1093/biostatistics/kxac007
Abstract: Considerable statistical work done on dynamic treatment regimes (DTRs) is in the frequentist paradigm, but Bayesian methods may have much to offer in this setting as they allow for the appropriate representation and propagation of… read more here.
Keywords: treatment regimes; dynamic treatment; bayesian inference; structural models ... See more keywords
Marginal structural models for multilevel clustered data.
Sign Up to like & getrecommendations! Published in 2022 at "Biostatistics"
DOI: 10.1093/biostatistics/kxac027
Abstract: Marginal structural models (MSMs), which adopt inverse probability treatment weighting in the estimating equations, are powerful tools to estimate the causal effects of time-varying exposures in the presence of time-dependent confounders. Motivated by the Conservation… read more here.
Keywords: models multilevel; time; clustered data; multilevel clustered ... See more keywords
Glucocorticoid exposure and the risk of serious infections in rheumatoid arthritis-a marginal structural model application.
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DOI: 10.1093/rheumatology/kead083
Abstract: OBJECTIVE Observational studies have reported an increased risk of infections associated with glucocorticoids in rheumatoid arthritis (RA), not supported by evidence from randomized controlled trials. Inappropriately accommodating time-varying exposure and confounding in observational studies might… read more here.
Keywords: rheumatology; rheumatoid arthritis; risk; marginal structural ... See more keywords
Exploring the Subtleties of Inverse Probability Weighting and Marginal Structural Models.
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DOI: 10.1097/ede.0000000000000813
Abstract: Since being introduced to epidemiology in 2000, marginal structural models have become a commonly used method for causal inference in a wide range of epidemiologic settings. In this brief report, we aim to explore three… read more here.
Keywords: inverse probability; structural models; marginal structural; epidemiology ... See more keywords
Marginal Structural Models Using Calibrated Weights With SuperLearner: Application to Type II Diabetes Cohort
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3175862
Abstract: As different scientific disciplines begin to converge on machine learning for causal inference, we demonstrate the application of machine learning algorithms in the context of longitudinal causal estimation using electronic health records. Our aim is… read more here.
Keywords: application; diabetes care; care provisions; type diabetes ... See more keywords