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Local likelihood with time‐varying additive hazards model
Author(s) -
Li Hui,
Yin Guosheng,
Zhou Yong
Publication year - 2007
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.5550350208
Subject(s) - estimator , mathematics , maximum likelihood , variance (accounting) , statistics , stability (learning theory) , restricted maximum likelihood , delta method , computer science , accounting , machine learning , business
The authors propose the local likelihood method for the time‐varying coefficient additive hazards model. They use the Newton‐Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time‐varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data from a laryngeal cancer clinical study.