Data-driven smooth tests of the proportional hazards assumption

KRAUS, David. Data-driven smooth tests of the proportional hazards assumption. Lifetime Data Analysis. Dordrecht: Springer, 2007, roč. 13, č. 1, s. 1-16. ISSN 1380-7870. Dostupné z: https://doi.org/10.1007/s10985-006-9027-8.

Základní údaje

Originální název

Data-driven smooth tests of the proportional hazards assumption

Autoři

KRAUS, David

Vydání

Lifetime Data Analysis, Dordrecht, Springer, 2007, 1380-7870

---

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 0.491

Označené pro přenos do RIV

Ne

DOI

https://doi.org/10.1007/s10985-006-9027-8

UT WoS

000244314200001

Klíčová slova anglicky

Cox model; Neyman's smooth test; proportional hazards assumption; Schwarz's selection rule

Příznaky

Mezinárodní význam, Recenzováno

---

Anotace

V originále

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.