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Babette Brumback
Researcher at University of Florida
Publications - 147
Citations - 12186
Babette Brumback is an academic researcher from University of Florida. The author has contributed to research in topics: Generalized linear mixed model & Sepsis. The author has an hindex of 34, co-authored 140 publications receiving 10438 citations. Previous affiliations of Babette Brumback include University of Florida College of Public Health and Health Professions & University of California, Los Angeles.
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Marginal Structural Models and Causal Inference in Epidemiology
TL;DR: In this paper, the authors introduce marginal structural models, a new class of causal models that allow for improved adjustment of confounding in observational studies with exposures or treatments that vary over time, when there exist time-dependent confounders that are also affected by previous treatment.
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Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.
TL;DR: The marginal structural Cox proportional hazards model is described and used to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study.
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Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments
TL;DR: This paper used a marginal structural Cox proportional hazards model to estimate the joint effect of AZT and prophylaxis therapy for Pneumocystis carinii pneumonia on the survival of HIV-positive men in the Multicenter AIDS Cohort Study.
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Smoothing spline models for the analysis of nested and crossed samples of curves
Babette Brumback,John Rice +1 more
TL;DR: In this paper, a class of models for an additive decomposition of groups of curves stratified by crossed and nested factors is introduced, and the model parameters are estimated using a highly efficient implementation of the EM algorithm for restricted maximum likelihood (REML) estimation based on a preliminary eigenvector decomposition.
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An overview of relations among causal modelling methods
TL;DR: Four major types of causal models for health-sciences research are provided: Graphical models, potential-outcome (counterfactual) models, sufficient-component cause models, and structural-equations models.