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Hypertabastic survival model.
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Theor Biol Med Model. 2007 Oct 26;4:40.PMID: 17963492 [PubMed - indexed for MEDLINE]Related articlesFree article
Accelerated hazards regression model and its adequacy for censored survival data.
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Estimating a treatment effect with the accelerated hazards models.
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[The application of Weibull parameter model to survival analysis of glioma]
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Zhang JJ, Wang M.
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Causal proportional hazards models and time-constant exposure in randomized clinical trials.
Loeys T, Goetghebeur E, Vandebosch A.
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A threshold regression mixture model for assessing treatment efficacy in a multiple myeloma clinical trial.
Lee ML, Chang M, Whitmore GA.
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Comparison of the Cox model and the regression tree procedure in analysing a randomized clinical trial.
Schmoor C, Ulm K, Schumacher M.
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Robustness of the quartiles of survival time and survival probability.
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On proportional hazards assumption under the random effects models.
Xu R, Gamst A.
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Mixtures of proportional hazards regression models.
Rosen O, Tanner M.
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Flexible boosting of accelerated failure time models.
Schmid M, Hothorn T.
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Analysis of time-dependent covariates in failure time data.
Aydemir U, Aydemir S, Dirschedl P.
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A Monte Carlo approach for change-point detection in the Cox proportional hazards model.
Liu M, Lu W, Shao Y.
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Practical methodology of meta-analysis of individual patient data using a survival outcome.
Katsahian S, Latouche A, Mary JY, Chevret S, Porcher R.
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Bootstrap analysis of multivariate failure time data.
Monaco J, Cai J, Grizzle J.
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First-event or marginal estimation of cause-specific hazards for analysing correlated multivariate failure-time data?
Tai BC, De Stavola BL, de Gruttola V, Gebski V, Machin D.
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Some permutation tests for survival data.
Sun Y, Sherman M.
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Comparing proportional hazards and accelerated failure time models for survival analysis.
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Adjusted variable plots for Cox's proportional hazards regression model.
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