activity
20182022
collaborators

5 papers

stat.ME2022

Variance estimation in pseudo-expected estimating equations for missing data

Giorgos Bakoyannis, Philani B. Mpofu, Andrea Broyles +1

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 wit…

stat.ME2021

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

Wenxian Zhou, Giorgos Bakoyannis, Ying Zhang +1

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 th…

stat.ME2019

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

Giorgos Bakoyannis

Frequently, clinical trials and observational studies involve complex event history data with multiple events. When the observations are independent, the analysis of such studies c…

stat.ME2019

Nonparametric tests for transition probabilities in nonhomogeneous Markov processes

Giorgos Bakoyannis

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 Mark…

stat.ME2018

Semiparametric regression and risk prediction with competing risks data under missing cause of failure

Giorgos Bakoyannis, Ying Zhang, Constantin T. Yiannoutsos

The cause of failure in cohort studies that involve competing risks is frequently incompletely observed. To address this, several methods have been proposed for the semiparametric…