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Survival analysis based on the proportional hazards model and survey data
Author(s) -
Boudreau Christian,
Lawless Jerald F.
Publication year - 2006
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550340202
Subject(s) - weighting , computer science , econometrics , sampling (signal processing) , survey data collection , statistics , sampling design , missing data , proportional hazards model , data mining , mathematics , sociology , medicine , population , demography , filter (signal processing) , computer vision , radiology
The authors propose methods based on the stratified Cox proportional hazards model that account for the fact that the data have been collected according to a complex survey design. The methods they propose are based on the theory of estimating equations in conjunction with empirical process theory. The authors also discuss issues concerning ignorable sampling design, and the use of weighted and unweighted procedures. They illustrate their methodology by an analysis of jobless spells in Statistics Canada's Survey of Labour and Income Dynamics. They discuss briefly problems concerning weighting, model checking, and missing or mismeasured data. They also identify areas for further research.