13 citations · 21 across the 9 of their papers we have counts for
9 papers
Semiparametric Regression for Misclassified Competing Risks Data
Theofanis Balanos, Constantin T. Yiannoutsos, Felix M. Pabon-Rodriguez +2
The analysis of competing risks data is often complicated by misclassification of the cause of failure. This issue can lead to seriously biased estimates and invalid conclusions. O…
Robustness intervals for competing risks analysis with causes of failure missing not at random
Giorgos Bakoyannis, Aristofanis Rontogiannis, Ying Zhang +3
Analysis of competing risks data is often complicated by the incomplete or selectively missing information on the cause of failure. Standard approaches typically assume that the ca…
Marginal Regression on Transient State Occupation Probabilities with Clustered Multistate Process Data
Wenxian Zhou, Giorgos Bakoyannis, Ying Zhang +1
Clustered multistate process data are commonly encountered in multicenter observational studies and clinical trials. A clinically important estimand with such data is the marginal…
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…
Estimating optimal individualized treatment rules with multistate processes
Giorgos Bakoyannis
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 refi…
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…
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…
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…
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…