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Full-Text Articles in Survival Analysis
Censored Data Regression In High-Dimension And Low-Sample Size Settings For Genomic Applications, Hongzhe Li
Censored Data Regression In High-Dimension And Low-Sample Size Settings For Genomic Applications, Hongzhe Li
UPenn Biostatistics Working Papers
New high-throughput technologies are generating various types of high-dimensional genomic and proteomic data and meta-data (e.g., networks and pathways) in order to obtain a systems-level understanding of various complex diseases such as human cancers and cardiovascular diseases. As the amount and complexity of the data increase and as the questions being addressed become more sophisticated, we face the great challenge of how to model such data in order to draw valid statistical and biological conclusions. One important problem in genomic research is to relate these high-throughput genomic data to various clinical outcomes, including possibly censored survival outcomes such as age …
Survival Analysis Methods In Genetic Epidemiology, Hongzhe Li
Survival Analysis Methods In Genetic Epidemiology, Hongzhe Li
UPenn Biostatistics Working Papers
Mapping genes for complex human diseases is a challenging problem due to the fact that many such diseases are due to both genetic and enviromental risk factors and many also exhibit phenotypic heterogeneity, such as variable age of onset. Information on variable age of disease onset is often a good indicator for disease heterogeneity and incorporation of such information together with enviromental risk factors into genetic analysis should lead to more powerful tests for genetic analysis. Due to the problem of censoring, survival analysis methods have proved to be very useful for genetic analysis. In this paper, I review some …