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Partially linear single index Cox regression model in nested case-control studies
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2013 (English)In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 67, 199-212 p.Article in journal (Refereed) Published
Abstract [en]

The nested case-control (NCC) design is widely used in epidemiologic studies as a cost-effective subcohort sampling method to study the association between a disease and its potential risk factors. NCC data are commonly analyzed using Thomas' partial likelihood approach under the Cox proportional hazards model assumption. However, the linear modeling form in the Cox model may be insufficient for practical applications, especially when there are a large number of risk factors under investigation. In this paper, we consider a partially linear single index proportional hazards model, which includes a linear component for covariates of interest to yield easily interpretable results and a nonparametric single index component to adjust for multiple confounders effectively. We propose to approximate the nonparametric single index function by polynomial splines and estimate the parameters of interest using an iterative algorithm based on the partial likelihood. Asymptotic properties of the resulting estimators are established. The proposed methods are evaluated using simulations and applied to an NCC study of ovarian cancer. 

Place, publisher, year, edition, pages
2013. Vol. 67, 199-212 p.
Keyword [en]
Nested case-control study, Risk-set sampling, Nonparametric regression, Nonlinear effect, Single index model
National Category
Computer and Information Science Mathematics Health Sciences
Identifiers
URN: urn:nbn:se:umu:diva-80416DOI: 10.1016/j.csda.2013.05.011ISI: 000323297000015OAI: oai:DiVA.org:umu-80416DiVA: diva2:651142
Available from: 2013-09-24 Created: 2013-09-17 Last updated: 2017-12-06Bibliographically approved

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Hallmans, Göran

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Nutritional ResearchDepartment of Biobank Research
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