14 citations · 17 across the 9 of their papers we have counts for
9 papers
Shared Frailty Methods for Complex Survival Data: A Review of Recent Advances
Malka Gorfine, David M. Zucker
Dependent survival data arise in many contexts. One context is clustered survival data, where survival data are collected on clusters such as families or medical centers. Dependent…
Revisiting the Cumulative Incidence Function With Competing Risks Data
David M. Zucker, Malka Gorfine
We consider estimation of the cumulative incidence function (CIF) in the competing risks Cox model. We study three methods. Methods 1 and 2 are existing methods while Method 3 is a…
Marginalized Frailty-Based Illness-Death Model: Application to the UK-Biobank Survival Data
Malka Gorfine, Nir Keret, Asaf Ben Arie +2
The UK Biobank is a large-scale health resource comprising genetic, environmental and medical information on approximately 500,000 volunteer participants in the UK, recruited at ag…
An improved fully nonparametric estimator of the marginal survival function based on case-control clustered data
David M. Zucker, Malka Gorfine
A case-control family study is a study where individuals with a disease of interest (case probands) and individuals without the disease (control probands) are randomly sampled from…
Cox Model with Covariate Measurement Error and Unknown Changepoint
Sarit Agami, David M. Zucker, Donna Spiegelman
The standard Cox model in survival analysis assumes that the covariate effect is constant across the entire covariate domain. However, in many applications, there is interest in co…
Estimation in the Cox Survival Regression Model with Covariate Measurement Error and a Changepoint
Sarit Agami, David M. Zucker, Donna Spiegelman
The Cox regression model is a popular model for analyzing the relationship between a covariate and a survival endpoint. The standard Cox model assumes a constant covariate effect a…