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Full-Text Articles in Statistical Models
Nonparametric And Semiparametric Inference For Models Of Tumor Size And Metastasis, Debashis Ghosh
Nonparametric And Semiparametric Inference For Models Of Tumor Size And Metastasis, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
There has been some recent work in the statistical literature for modelling the relationship between the size of primary cancers and the occurrences of metastases. While nonparametric methods have been proposed for estimation of the tumor size distribution at which metastatic transition occurs, their asymptotic properties have not been studied. In addition, no testing or regression methods are available so that potential confounders and prognostic factors can be adjusted for. We develop a unified approach to nonparametric and semiparametric analysis of modelling tumor size-metastasis data in this article. An equivalence between the models considered by previous authors with survival data …
Model Checking Techniques For Regression Models In Cancer Screening, Debashis Ghosh
Model Checking Techniques For Regression Models In Cancer Screening, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
There has been much work on developing statistical procedures for associating tumor size with the probability of detecting a metastasis. Recently, Ghosh (2004) developed a unified statistical framework in which equivalences with censored data structures and models for tumor size and metastasis were examined. Based on this framework, we consider model checking techniques for semiparametric regression models in this paper. The procedures are for checking the additive hazards model. Goodness of fit methods are described for assessing functional form of covariates as well as the additive hazards assumption. The finite-sample properties of the methods are assessed using simulation studies.