Semiparametric analysis of interval‐censored failure time data with outcome‐dependent observation schemes

Yayuan Zhu, Ziqi Chen and Jerald F. Lawless

Scandinavian Journal of Statistics, 2022, vol. 49, issue 1, 236-264

Abstract: Disease progression is often monitored by intermittent follow‐up “visits” in longitudinal cohort studies, resulting in interval‐censored failure time outcomes. Furthermore, the timing and frequency of visits is often found related to a person's history of disease‐related variables in practice. This article develops a semiparametric estimation approach using weighted binomial regression and a kernel smoother to analyze interval‐censored failure time data. Visit times are allowed to be subject‐specific and outcome‐dependent. We consider a collection of widely used semiparametric regression models, including additive hazards and linear transformation models. For additive hazards models, the nonparametric component has a closed‐form estimator and the estimators of regression coefficients are shown to be asymptotically multivariate normal with sandwich‐type covariance matrices. Simulations are conducted to examine the finite sample performance of the proposed estimators. A data set from the Toronto Psoriatic Arthritis (PsA) Cohort Study is used to illustrate the proposed methodology.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/sjos.12511

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:49:y:2022:i:1:p:236-264

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().