Nonparametric Estimation of Marginal Temporal Functionals in a Multi-State Model

Somnath Datta and A. Nicole Ferguson ()
Additional contact information
Somnath Datta: University of Louisville
A. Nicole Ferguson: University of Louisville

Chapter Chapter 16 in Recent Advances in System Reliability, 2012, pp 219-235 from Springer

Abstract: Abstract Multi-state models are generalizations of traditional survival analysis and reliability studies. They are common in medical and engineering applications where a subject (say a patient or a machine) is moving through a succession of states (each representing a stage of disease progression or the condition of a machine) with time. In addition, several key questions in event history analysis and multi-variate survival analysis can be formulated in terms of a staged system making the use of multi-state models extremely broad. While the use of parametric and semiparametric models to various transitions are the most common approaches to study multi-state data, this overview paper deals entirely with nonparametric methods. In addition, we limit our exposition to estimation questions related to marginal models rather than conditional (e.g., regression) models. We review a number of methods from the recent past dealing with estimation of hazards, transition and state occupation probabilities, state entry, exit and waiting time distributions and also discuss some ongoing and future research problems on these topics. Various forms of censoring that occur in the collection of multi-state data are discussed including right and interval censoring.

Keywords: Multi-state models; Survival; Multi-stage; Censoring; Current status; Interval censoring; State occupation probabilities (search for similar items in EconPapers)
Date: 2012
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:ssrchp:978-1-4471-2207-4_16

Ordering information: This item can be ordered from
http://www.springer.com/9781447122074

DOI: 10.1007/978-1-4471-2207-4_16

Access Statistics for this chapter

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