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I-Boost is a statistical boosting method that integrates multiple types of high-dimensional genomics data with clinical data for predicting survival time.
Simulation data sets and codes to perform all the analyses in the paper: Wong KY, Fan C, Tanioka M, Parker JS, Nobel AB, Zeng D, Lin DY, Perou CM. I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms. 2019.
Perform estimation and inference for clustered current status data with informative cluster size using the method proposed by Lam et al. (2021) <DOI: https://doi.org/10.1002/sim.8910>.
A general model for the joint analysis of multivariate longitudinal data and survival time
Penalized regression for multiple types of many features with missing data using expectation-maximization (EM) algorithm.
This directory contains the codes to perform all the analyses and reproduce all the figures and tables presented in the paper: Ng HM, Jiang BY, Wong KY. Penalized estimation of a class of single-index varying-coefficient models for integrative genomic analysis. 2022.
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