Fitting semiparametric accelerated failure time models for nested case–control data

ABSTRACT

A nested case–control (NCC) study is an efficient cohort-sampling design in which a subset of controls are sampled from the risk set at each event time. Since covariate measurements are taken only for the sampled subjects, time and efforts of conducting a full scale cohort study can be saved. In this paper, we consider fitting a semiparametric accelerated failure time model to failure time data from a NCC study. We propose to employ an efficient induced smoothing procedure for rank-based estimating method for regression parameters estimation. For variance estimation, we propose to use an efficient resampling method that utilizes the robust sandwich form. We extend our proposed methods to a generalized NCC study that allows a sampling of cases. Finite sample properties of the proposed estimators are investigated via an extensive stimulation study. An application to a tumor study illustrates the utility of the proposed method in routine data analysis.

KEYWORDS:

• Cohort-sampling
• induced smoothing
• multiplier bootstrap
• survival analysis
• weighted estimating equations

AMS SUBJECT CLASSIFICATION:

• 2N01
• 62N02
• 62D05
• 62P10

Acknowledgement

The author thanks Jun Yan at the University of Connecticut for helpful discussions. The author also wishes to thank the Editor, an Associate Editor, and a referee for their constructive comments which led to substantial improvement of the paper.

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Funding

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education [grant number NRF-2014R1A1A2055898].