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@article{1324011,
author = {Kraus, David},
article_location = {Dordrecht},
article_number = {1},
doi = {http://dx.doi.org/10.1007/s10985-006-9027-8},
keywords = {Cox model; Neyman's smooth test; proportional hazards assumption; Schwarz's selection rule},
language = {eng},
issn = {1380-7870},
journal = {Lifetime Data Analysis},
title = {Data-driven smooth tests of the proportional hazards assumption},
volume = {13},
year = {2007}
}
TY - JOUR
ID - 1324011
AU - Kraus, David
PY - 2007
TI - Data-driven smooth tests of the proportional hazards assumption
JF - Lifetime Data Analysis
VL - 13
IS - 1
SP - 1-16
EP - 1-16
PB - Springer
SN - 13807870
KW - Cox model
KW - Neyman's smooth test
KW - proportional hazards assumption
KW - Schwarz's selection rule
N2 - A new test of the proportional hazards assumption in the Cox model is proposed. The idea is based on Neyman's smooth tests. The Cox model with proportional hazards (i.e. time-constant covariate effects) is embedded in a model with a smoothly time-varying covariate effect that is expressed as a combination of some basis functions (e.g., Legendre polynomials, cosines). Then the smooth test is the score test for significance of these artificial covariates. Furthermore, we apply a modification of Schwarz's selection rule to choosing the dimension of the smooth model (the number of the basis functions). The score test is then used in the selected model. In a simulation study, we compare the proposed tests with standard tests based on the score process.
ER -
KRAUS, David. Data-driven smooth tests of the proportional hazards assumption. \textit{Lifetime Data Analysis}. Dordrecht: Springer, roč.~13, č.~1, s.~1-16. ISSN~1380-7870. doi:10.1007/s10985-006-9027-8. 2007.
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