Versatile estimation in censored single-index hazards regression

Chin-Tsang Chiang (), Shao-Hsuan Wang and Ming-Yueh Huang
Additional contact information
Chin-Tsang Chiang: National Taiwan University
Shao-Hsuan Wang: National Taiwan University
Ming-Yueh Huang: National Taiwan University

Annals of the Institute of Statistical Mathematics, 2018, vol. 70, issue 3, No 2, 523-551

Abstract: Abstract One attractive advantage of the presented single-index hazards regression is that it can take into account possibly time-dependent covariates. In such a model formulation, the main theme of this research is to develop a theoretically valid and practically feasible estimation procedure for the index coefficients and the induced survival function. In particular, compared with the existing pseudo-likelihood approaches, our one proposes an automatic bandwidth selection and suppresses an influence of outliers. By making an effective use of the considered versatile survival process, we further reduce a substantial finite-sample bias in the Chambless-Diao type estimator of the most popular time-dependent accuracy summary. The asymptotic properties of estimators and data-driven bandwidths are also established under some suitable conditions. It is found in simulations that the proposed estimators and inference procedures exhibit quite satisfactory performances. Moreover, the general applicability of our methodology is illustrated by two empirical data.

Keywords: Accuracy measure; Conditional survival function; Cross-validation; Kaplan–Meier estimator; Pseudo-integrated least squares estimator; Pseudo-maximum likelihood estimator; Single-index hazards model; U-statistic (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10463-017-0600-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:aistmt:v:70:y:2018:i:3:d:10.1007_s10463-017-0600-6

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10463/PS2

DOI: 10.1007/s10463-017-0600-6

Access Statistics for this article

Annals of the Institute of Statistical Mathematics is currently edited by Tomoyuki Higuchi

More articles in Annals of the Institute of Statistical Mathematics from Springer, The Institute of Statistical Mathematics
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().