Efficiently Weighted Estimating Equations with Application to Proportional Excess Hazards

Peter D. Sasieni
Additional contact information
Peter D. Sasieni: Imperial Cancer Research Fund, Dept. of Math, Stats and Epidemiology

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 281-289 from Springer

Abstract: Abstract A general approach to estimation, that can lead to efficient estimation in two stages, is presented. The method will not always be available, but sufficient conditions for efficiency are provided together with four examples of its use: (1) estimation of the odds ratio in 1:M matched case-control studies with a dichotomous exposure variable; (2) estimation of the relative hazard in a two-sample survival setting; (3) estimation of the regression parameters in the proportional excess hazards model; and (4) estimation in a partly linear parametric additive hazards model. The method depends upon finding a family of weighted estimating equations, which includes a simple initial equation yielding a consistent estimate and also an equation that yields an efficient estimate, provided the optiomal weights are used.

Keywords: Efficient Score; Nuisance Parameter; Partial Likelihood; Predictable Process; Conditional Likelihood (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-1-4757-5654-8_37

Ordering information: This item can be ordered from
http://www.springer.com/9781475756548

DOI: 10.1007/978-1-4757-5654-8_37

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().