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Testing goodness-of-fit for the proportional hazards model based on nested case-control data.

ABSTRACT: Nested case-control sampling is a popular design for large epidemiological cohort studies due to its cost effectiveness. A number of methods have been developed for the estimation of the proportional hazards model with nested case-control data; however, the evaluation of modeling assumption is less attended. In this article, we propose a class of goodness-of-fit test statistics for testing the proportional hazards assumption based on nested case-control data. The test statistics are constructed based on asymptotically mean-zero processes derived from Samuelsen's maximum pseudo-likelihood estimation method. In addition, we develop an innovative resampling scheme to approximate the asymptotic distribution of the test statistics while accounting for the dependent sampling scheme of nested case-control design. Numerical studies are conducted to evaluate the performance of our proposed approach, and an application to the Wilms' Tumor Study is given to illustrate the methodology.

SUBMITTER: Lu W

PROVIDER: S-EPMC4276544 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Testing goodness-of-fit for the proportional hazards model based on nested case-control data.

Lu Wenbin W Liu Mengling M Chen Yi-Hau YH

Biometrics 20141008 4

Nested case-control sampling is a popular design for large epidemiological cohort studies due to its cost effectiveness. A number of methods have been developed for the estimation of the proportional hazards model with nested case-control data; however, the evaluation of modeling assumption is less attended. In this article, we propose a class of goodness-of-fit test statistics for testing the proportional hazards assumption based on nested case-control data. The test statistics are constructed ...[more]

PMID: 25298193

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