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Articles

Semiparametric Bayesian analysis of high-dimensional censored outcome data

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Pages 194-204 | Received 21 May 2017, Accepted 21 Oct 2017, Published online: 10 Nov 2017

Figures & data

Figure 1. Estimated mean versus true mean of log-survival time for the n = 10, 000 individuals considered in the simulation study.

Figure 1. Estimated mean versus true mean of log-survival time for the n = 10, 000 individuals considered in the simulation study.

Figure 2. Posterior densities of σ (top) and τ (bottom) for the simulation study. The true parameter values are σ = 0.05 and τ = 0.4.

Figure 2. Posterior densities of σ (top) and τ (bottom) for the simulation study. The true parameter values are σ = 0.05 and τ = 0.4.

Table 1. Computational time comparison on simulated data.

Figure 3. Posterior densities of the factor effect of black (top) and American Indian (bottom) races for SEER breast cancer New Mexico data.

Figure 3. Posterior densities of the factor effect of black (top) and American Indian (bottom) races for SEER breast cancer New Mexico data.

Table 2. 95% posterior credible intervals of selected parameters for the New Mexico breast cancer data.

Figure 4. Posterior densities of the factor effect of tumor grade 2 at diagnosis (top) and tumor 4 at diagnosis (bottom).

Figure 4. Posterior densities of the factor effect of tumor grade 2 at diagnosis (top) and tumor 4 at diagnosis (bottom).

Figure 5. Estimates of the county-specific random effects for New Mexico. The labels are the county names.

Figure 5. Estimates of the county-specific random effects for New Mexico. The labels are the county names.

Figure 6. Standard errors of the county-specific random effects for New Mexico. The labels are the county names.

Figure 6. Standard errors of the county-specific random effects for New Mexico. The labels are the county names.

Figure 7. Posterior density of the individual-specific error distribution F defined in Equation (Equation11). See the text for the interpretation of F. The narrow lines represent margins of 2 posterior standard deviations.

Figure 7. Posterior density of the individual-specific error distribution F defined in Equation (Equation11(11) ). See the text for the interpretation of F. The narrow lines represent margins of 2 posterior standard deviations.

Table 3. Mixed effects cox regression for the New Mexico breast cancer data.

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