Print Email Facebook Twitter Bootstrapping in the Cox-model with interval censored observations Title Bootstrapping in the Cox-model with interval censored observations Author Gouwens, Sigur (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Jongbloed, Geurt (mentor) Degree granting institution Delft University of Technology Programme Applied Mathematics Date 2019-12-01 Abstract In this study the interval censoring case 2 model combined with the Cox model is considered. The event-time distribution function is modeled nonparametrically. Two algorithms are proposed to estimate the event-time distribution function together with the Cox coefficients. Kernel smoothing is applied to the non-parametric MLE of the event-time distribution resulting in the smoothed MLE (SMLE). A two-step method for choosing the smoothing bandwidth based on minimising the MSE is introduced. Given the SMLE, the precision of the MLE is tested using bootstrap simulations. New event-times are sampled from the SMLE which are then used to compute bootstrap estimates of the event-time distribution. This is done for multiple sample sizes to observe large sample behaviour. This study suggests that larger sample sizes lead tobetter estimates. Monte Carlo simulations and the bootstrap simulations agree on the bandwidth and the large sample distribution of pointwise estimates of the event-time distribution. Subject Survival analysisCox modelInterval CensoringBootstrap To reference this document use: http://resolver.tudelft.nl/uuid:2e7bbcb9-b83a-43fa-8c5f-b1f684b48ac7 Part of collection Student theses Document type master thesis Rights © 2019 Sigur Gouwens Files PDF MSc_Thesis_Sigur_Gouwens.pdf 920.9 KB Close viewer /islandora/object/uuid:2e7bbcb9-b83a-43fa-8c5f-b1f684b48ac7/datastream/OBJ/view