Results 311 to 320 of about 1,084,291 (346)
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2003
Publisher Summary This chapter discusses inference problems for competing risks and illustrates methods using a typical competing risk data set taken from an International Bone Marrow Transplant (BMT) Registry study of alternative donor bone marrow transplantation reported by Szydlo et al.
Ruta Bajorunaite, John P. Klein
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Publisher Summary This chapter discusses inference problems for competing risks and illustrates methods using a typical competing risk data set taken from an International Bone Marrow Transplant (BMT) Registry study of alternative donor bone marrow transplantation reported by Szydlo et al.
Ruta Bajorunaite, John P. Klein
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Biometrika, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jason P. Fine +2 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jason P. Fine +2 more
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Dynamic prediction by landmarking in competing risks
Statistics in Medicine, 2012We propose an extension of the landmark model for ordinary survival data as a new approach to the problem of dynamic prediction in competing risks with time‐dependent covariates. We fix a set of landmark time points tLM within the follow‐up interval. For each of these landmark time points tLM, we create a landmark data set by selecting individuals at ...
Nicolaie, M.A. +4 more
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Statistical Methods for Dependent Competing Risks
Lifetime Data Analysis, 1995Many biological and medical studies have as a response of interest the time to occurrence of some event, X, such as the occurrence of cessation of smoking, conception, a particular symptom or disease, remission, relapse, death due to some specific disease, or simply death.
Melvin L. Moeschberger, John P. Klein
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2016
In the previous chapters we considered various statistical techniques that model the time to a particular event of interest. In this chapter, we consider competing risks models, which extend the previously described models to survival data with several distinct types of target events.
Matthias Schmid, Gerhard Tutz
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In the previous chapters we considered various statistical techniques that model the time to a particular event of interest. In this chapter, we consider competing risks models, which extend the previously described models to survival data with several distinct types of target events.
Matthias Schmid, Gerhard Tutz
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Competing Risks in Low-Risk Breast Cancer
American Society of Clinical Oncology Educational Book, 2013In recent years a growing amount of data on prognostic features of breast cancer has allowed for identification of tumors with a very low risk of recurrence. Markers used to predict the risk of distant spread include classic clinicopathologic features as well as newer tumor gene signatures, which have been validated and are being used in cohorts of ...
Kathrin Strasser-Weippl, Paul E. Goss
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Competing Risks Quantile Regression
Journal of the American Statistical Association, 2009Quantile regression has emerged as a significant extension of traditional linear models and its potential in survival applications has recently been recognized. In this paper we study quantile regression with competing risks data, formulating the model based on conditional quantiles defined using the cumulative incidence function, which includes as a ...
Peng, Limin, Fine, Jason P.
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Identifiability Crises in Competing Risks
International Statistical Review / Revue Internationale de Statistique, 1994Summary: Difficulties and pitfalls of dependency modelling in Statistics are very well illustrated by problems of identifiability in Competing Risks. This paper gives a review of such problems with examples intended to animate the theoretical results. The problems covered arise through the traditional way of modelling Competing Risks via latent failure
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An Introduction to Competing Risks Analysis
Revista Española de Cardiología (English Edition), 2011The need to develop treatments and/or programs specific to a disease requires the analysis of outcomes to be specific to that disease. Such endpoints as heart failure, death due to a specific disease, or control of local disease in cancer may become impossible to observe due to a prior occurrence of a different type of event (such as death from another
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2000
The term competing risks refers to cause of death models. Competing risks have been introduced and illustrated as a multi-state model in Figure 1.7 and discussed previously, in Sections 1.10, 3.3.9, and Chapter 5; but such data present special challenges, and therefore are considered separately in this chapter.
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The term competing risks refers to cause of death models. Competing risks have been introduced and illustrated as a multi-state model in Figure 1.7 and discussed previously, in Sections 1.10, 3.3.9, and Chapter 5; but such data present special challenges, and therefore are considered separately in this chapter.
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