An application of nonprarametric Cox regression model in reliability analysis: a case study

Petr Volf

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Displaying similar documents to “An application of nonprarametric Cox regression model in reliability analysis: a case study”

Statistical models to study subtoxic concentrations for some standard mutagens in three colon cancer cell lines.

Xavier Bardina, Laura Fernández, Elisabet Piñeiro, Jordi Surrallés, Antonia Velázquez (2006)

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The aim of this work is to propose models to study the toxic effect of different concentrations of some standard mutagens in different colon cancer cell lines. We find estimates and, by means of an inverse regression problem, confidence intervals for the subtoxic concentration, that is the concentration that reduces by thirty percent the number of colonies obtained in the absence of mutagen.

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Study of Bootstrap Estimates in Cox Regression Model with Delayed Entry

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In most clinical studies, patients are observed for extended time periods to evaluate influences in treatment such as drug treatment, approaches to surgery, etc. The primary event in these studies is death, relapse, adverse drug reaction, or development of a new disease. The follow-up time may range from few weeks to many years. Although these studies are long term, the number of observed events is small. Longitudinal studies have increased the importance of statistical methods for time-to...

Bayesian approach for joint longitudinal and time-to-event data with survival fraction.

Bakar, Mohd Rizam Abu, Salah, Khalid A., Ibrahim, Noor Akma, Haron, Kassim (2009)

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Spatial correlation of gene expression measures in tissue microarry core analysis.

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A construction of a realistic statistical model of lung cancer risk and progression is proposed. The essential elements of the model are genetic and behavioral determinants of susceptibility, progression of the disease from precursor lesions through early (localized) tumors to disseminated disease, detection by various modalities, and medical intervention. Using model estimates as a foundation, mortality reduction caused by early-detection and intervention programs can be predicted under...