Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates

J. F. Lawless ()
Additional contact information
J. F. Lawless: University of Waterloo

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2018, vol. 24, issue 1, No 3, 28-44

Abstract: Abstract Two- or multi-phase study designs are often used in settings involving failure times. In most studies, whether or not certain covariates are measured on an individual depends on their failure time and status. For example, when failures are rare, case–cohort or case–control designs are used to increase the number of failures relative to a random sample of the same size. Another scenario is where certain covariates are expensive to measure, so they are obtained only for selected individuals in a cohort. This paper considers such situations and focuses on cases where we wish to test hypotheses of no association between failure time and expensive covariates. Efficient score tests based on maximum likelihood are developed and shown to have a simple form for a wide class of models and sampling designs. Some numerical comparisons of study designs are presented.

Keywords: Cohort sampling designs; Generalized linear transformation models; Genetic association tests; Missing data (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s10985-016-9386-8 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:lifeda:v:24:y:2018:i:1:d:10.1007_s10985-016-9386-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10985

DOI: 10.1007/s10985-016-9386-8

Access Statistics for this article

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data is currently edited by Mei-Ling Ting Lee

More articles in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().