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Semiparametric lack-of-fit tests in an additive hazard regression model

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Abstract

In the semiparametric additive hazard regression model of McKeague and Sasieni (Biometrika 81: 501–514), the hazard contributions of some covariates are allowed to change over time, without parametric restrictions (Aalen model), while the contributions of other covariates are assumed to be constant. In this paper, we develop tests that help to decide which of the covariate contributions indeed change over time. The remaining covariates may be modelled with constant hazard coefficients, thus reducing the number of curves that have to be estimated nonparametrically. Several bootstrap tests are proposed. The behavior of the tests is investigated in a simulation study. In a practical example, the tests consistently identify covariates with constant and with changing hazard contributions.

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Authors and Affiliations

  1. School of Statistics, University of Minnesota, Minneapolis, MN, 55455, USA

    Birgit Grund

  2. Weierstraß-Institut für Angewandte Analysis und Stochastik, D-10117, Berlin, Germany

    Jörg Polzehl

Authors
  1. Birgit Grund
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  2. Jörg Polzehl
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Grund, B., Polzehl, J. Semiparametric lack-of-fit tests in an additive hazard regression model. Statistics and Computing 11, 323–335 (2001). https://doi.org/10.1023/A:1011968919773

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