Literature DB >> 9544517

Prediction of cumulative incidence function under the proportional hazards model.

S C Cheng1, J P Fine, L J Wei.   

Abstract

In the presence of dependent competing risks in survival analysis, the Cox model can be utilized to examine the covariate effects on the cause-specific hazard function for the failure type of interest. For this situation, the cumulative incidence function provides an intuitively appealing summary curve for marginal probabilities of this particular event. In this paper, we show how to construct confidence intervals and bands for such a function under the Cox model for future patients with certain covariates. Our proposals are illustrated with data from a prostate cancer trial.

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Year:  1998        PMID: 9544517

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  41 in total

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Review 5.  Inference for outcome probabilities in multi-state models.

Authors:  Per Kragh Andersen; Maja Pohar Perme
Journal:  Lifetime Data Anal       Date:  2008-09-13       Impact factor: 1.588

6.  Modeling cumulative incidence function for competing risks data.

Authors:  Mei-Jie Zhang; Xu Zhang; Thomas H Scheike
Journal:  Expert Rev Clin Pharmacol       Date:  2008-05-01       Impact factor: 5.045

7.  Regression analysis for cumulative incidence probability under competing risks and left-truncated sampling.

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Journal:  Lifetime Data Anal       Date:  2011-08-11       Impact factor: 1.588

8.  Smoothed Rank Regression for the Accelerated Failure Time Competing Risks Model with Missing Cause of Failure.

Authors:  Zhiping Qiu; Alan T K Wan; Yong Zhou; Peter B Gilbert
Journal:  Stat Sin       Date:  2019-01       Impact factor: 1.261

9.  Competing risk regression models for epidemiologic data.

Authors:  Bryan Lau; Stephen R Cole; Stephen J Gange
Journal:  Am J Epidemiol       Date:  2009-06-03       Impact factor: 4.897

10.  Importance of age of onset in pancreatic cancer kindreds.

Authors:  Kieran A Brune; Bryan Lau; Emily Palmisano; Marcia Canto; Michael G Goggins; Ralph H Hruban; Alison P Klein
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