Výsledky vyhledávání - "Bakoyannis Giorgos"

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Marginal Regression on Transient State Occupation Probabilities with Clustered Multistate Process Data

Autor: Zhou, Wenxian, Bakoyannis, Giorgos, Zhang, Ying, Yiannoutsos, Constantin T

Clustered multistate process data are commonly encountered in multicenter observational studies and clinical trials. A clinically important estimand with such data is the marginal probability of being in a particular transient state as a function of

Externí odkaz: http://arxiv.org/abs/2209.00804

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Variance estimation in pseudo-expected estimating equations for missing data

Autor: Bakoyannis, Giorgos, Mpofu, Philani B., Broyles, Andrea, Dixon, Brian B.

Missing data is a common challenge in biomedical research. This fact, along with growing dataset volumes of the modern era, make the issue of computationally-efficient analysis with missing data of crucial practical importance. A general computationa

Externí odkaz: http://arxiv.org/abs/2204.09818

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Estimating optimal individualized treatment rules with multistate processes

Autor: Bakoyannis, Giorgos

Multistate process data are common in studies of chronic diseases such as cancer. These data are ideal for precision medicine purposes as they can be leveraged to improve more refined health outcomes, compared to standard survival outcomes, as well a

Externí odkaz: http://arxiv.org/abs/2204.09785

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Semiparametric Marginal Regression for Clustered Competing Risks Data with Missing Cause of Failure

Autor: Zhou, Wenxian, Bakoyannis, Giorgos, Zhang, Ying, Yiannoutsos, Constantin T.

Clustered competing risks data are commonly encountered in multicenter studies. The analysis of such data is often complicated due to informative cluster size, a situation where the outcomes under study are associated with the size of the cluster. In

Externí odkaz: http://arxiv.org/abs/2104.09090

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Nonparametric analysis of nonhomogeneous multi-state processes based on clustered observations

Autor: Bakoyannis, Giorgos

Frequently, clinical trials and observational studies involve complex event history data with multiple events. When the observations are independent, the analysis of such studies can be based on standard methods for multi-state models. However, the i

Externí odkaz: http://arxiv.org/abs/1912.00487

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Nonparametric tests for transition probabilities in nonhomogeneous Markov processes

Autor: Bakoyannis, Giorgos

This paper proposes nonparametric two-sample tests for the direct comparison of the probabilities of a particular transition between states of a continuous time nonhomogeneous Markov process with a finite state space. The proposed tests are a linear

Externí odkaz: http://arxiv.org/abs/1904.03517

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