Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Efficient estimation of the distribution of time to composite endpoint when some endpoints are only partially observed

Daniel, Rhian ORCID: https://orcid.org/0000-0001-5649-9320 and Tsiatis, Anastasios A. 2013. Efficient estimation of the distribution of time to composite endpoint when some endpoints are only partially observed. Lifetime Data Analysis 19 (4) , pp. 513-546. 10.1007/s10985-013-9261-9

Full text not available from this repository.

Abstract

Two common features of clinical trials, and other longitudinal studies, are (1) a primary interest in composite endpoints, and (2) the problem of subjects withdrawing prematurely from the study. In some settings, withdrawal may only affect observation of some components of the composite endpoint, for example when another component is death, information on which may be available from a national registry. In this paper, we use the theory of augmented inverse probability weighted estimating equations to show how such partial information on the composite endpoint for subjects who withdraw from the study can be incorporated in a principled way into the estimation of the distribution of time to composite endpoint, typically leading to increased efficiency without relying on additional assumptions above those that would be made by standard approaches. We describe our proposed approach theoretically, and demonstrate its properties in a simulation study.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Subjects: R Medicine > R Medicine (General)
Uncontrolled Keywords: Augmented inverse probability weighted estimator; Composite endpoint; Missing data; Nelson–Aalen estimator; Semi-parametric efficiency; Withdrawal
Publisher: Springer
ISSN: 1380-7870
Last Modified: 03 Nov 2022 09:48
URI: https://orca.cardiff.ac.uk/id/eprint/106069

Citation Data

Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item