KRAUS, David. Data-driven smooth tests of the proportional hazards assumption. Lifetime Data Analysis. Dordrecht: Springer, vol. 13, No 1, p. 1-16. ISSN 1380-7870. doi:10.1007/s10985-006-9027-8. 2007.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Data-driven smooth tests of the proportional hazards assumption
Authors KRAUS, David.
Edition Lifetime Data Analysis, Dordrecht, Springer, 2007, 1380-7870.
Other information
Original language English
Type of outcome Article in a journal
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 0.491
Doi http://dx.doi.org/10.1007/s10985-006-9027-8
UT WoS 000244314200001
Keywords in English Cox model; Neyman's smooth test; proportional hazards assumption; Schwarz's selection rule
Tags International impact, Reviewed
Changed by Changed by: doc. Mgr. David Kraus, Ph.D., učo 238224. Changed: 12/1/2016 16:44.
Abstract
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.
PrintDisplayed: 29/3/2024 02:53