SEMIPARAMETRIC ANALYSIS OF INTERVAL-CENSORED DATA SUBJECT TO INACCURATE DIAGNOSES WITH A TERMINAL EVENT. [PDF]
Deng Y, Zeng D, Wang Y.
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A Support vector machine-based mixture cure model for mixed case interval censored data. [PDF]
Pal S, Aselisewine W.
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Deep learning for the change-point Cox model with current status data. [PDF]
Huang Q, Feng A, Wu Q, Tong X.
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Cure rate estimation with insufficient follow-up: A median-based bootstrap correction approach. [PDF]
Ibi Y, Omori T.
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Tobit modeling for dependent-sample t-tests and moderated regression with ceiling or floor data. [PDF]
Wang L, Li R.
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Accommodating the Analysis Model in Multiple Imputation for the Weibull Mixture Cure Model: Performance Under Penalized Likelihood. [PDF]
Xu C, Briollais L, Andrulis IL, Bull SB.
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Wasserstein GAN-based estimation for conditional distribution function with current status data. [PDF]
Su W, Liu C, Yin G, Huang J.
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Fast standard error estimation for joint models of longitudinal and time-to-event data based on stochastic EM algorithms. [PDF]
Yu T, Wu L, Bosch RJ, Smith DM, Wang R.
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A practical overview and statistical analysis of interval-censored data in cancer. [PDF]
Dey T +6 more
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Using Quadratic Programming to Reconstruct Data From Published Survival and Competing Risks Analyses. [PDF]
Titman AC.
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