@book{Liero2010,
  author    = {Liero, Hannelore},
  title     = {Estimation and testing the effect of covariates in accelerated life time models under censoring},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52823},
  publisher      = {Universit{\"a}t Potsdam},
  year      = {2010},
  abstract  = {The accelerated lifetime model is considered. To test the influence of the covariate we transform the model in a regression model. Since censoring is allowed this approach leads to a goodness-of-fit problem for regression functions under censoring. So nonparametric estimation of regression functions under censoring is investigated, a limit theorem for a L2-distance is stated and a test procedure is formulated. Finally a Monte Carlo procedure is proposed.},
  language  = {en}
}
@unpublished{Liero2003,
  author    = {Liero, Hannelore},
  title     = {Testing the Hazard Rate, Part I},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-51510},
  year      = {2003},
  abstract  = {We consider a nonparametric survival model with random censoring. To test whether the hazard rate has a parametric form the unknown hazard rate is estimated by a kernel estimator. Based on a limit theorem stating the asymptotic normality of the quadratic distance of this estimator from the smoothed hypothesis an asymptotic ®-test is proposed. Since the test statistic depends on the maximum likelihood estimator for the unknown parameter in the hypothetical model properties of this parameter estimator are investigated. Power considerations complete the approach.},
  language  = {en}
}