On MM algorithms for Cox model with right-censored data

Lulu Zhang; Xifen Huang

doi:10.1117/12.2642737

28 July 2022 On MM algorithms for Cox model with right-censored data

Lulu Zhang, Xifen Huang

Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 1230307 (2022) https://doi.org/10.1117/12.2642737
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China

Abstract

The Cox models have been widely used for analyzing right-censored survival data based on the partial likelihood functions. Despite its success in estimating the regression parameters, the partial likelihood ignores the existence of the unspecified cumulative hazard rate. This article focuses on the complete likelihood function which considers the estimation of both the regression parameters and the nonparametric components. To estimate both parametric and nonparametric components, we propose the minorization-maximization (MM) algorithm to separate the regression parameters and nonparametric components. Then the high-dimensional objective function is decomposed into a sum of low-dimensional functions which avoids the difficulty of large matrix inversion. Simulation studies demonstrate that the algorithms perform well in various cases. The breast cancer data are used to illustrate the proposed algorithms as well.

Citation Download Citation

Lulu Zhang and Xifen Huang "On MM algorithms for Cox model with right-censored data", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 1230307 (28 July 2022); https://doi.org/10.1117/12.2642737

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available