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Misspecified Proportional Hazard Models
Biometrika, 1986Let \((N_ i(t)\), \(t\geq 0\), \(i=1,...,n)\) be a counting process in which \(N_ i(t)\) records the number of failures in [0,t] for i-th item, and let \(Y_ i(t)\lambda_ 0(t) \exp (\beta Z_ i)\) \((i=1,...,n)\) be a random intensity process (for \(N_ i)\).
Struthers, C. A., Kalbfleisch, J. D.
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Tree-Structured Proportional Hazards Regression Modeling
Biometrics, 1994A method for fitting piecewise proportional hazards models to censored survival data is described. Stratification is performed recursively, using a combination of statistical tests and residual analysis. The bootstrap is employed to keep the probability of a Type I error (the error of discovering two or more strata when there is only one) of the method
Ahn, Hongshik, Loh, Wei-Yin
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2008
The estimation of duration models has been the subject of significant research in econometrics since the late 1970s. Cox (1972) proposed the use of proportional hazard models in biostatistics and they were soon adopted for use in economics. Since Lancaster (1979), it has been recognized among economists that it is important to account for unobserved ...
Jerry A. Hausman, Tiemen M. Woutersen
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The estimation of duration models has been the subject of significant research in econometrics since the late 1970s. Cox (1972) proposed the use of proportional hazard models in biostatistics and they were soon adopted for use in economics. Since Lancaster (1979), it has been recognized among economists that it is important to account for unobserved ...
Jerry A. Hausman, Tiemen M. Woutersen
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2021
We consider several models that describe survival in the presence of observable covariates, these covariates measuring subject heterogeneity. The most general situation can be described by a model with a parameter of high, possibly unbounded, dimension.
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We consider several models that describe survival in the presence of observable covariates, these covariates measuring subject heterogeneity. The most general situation can be described by a model with a parameter of high, possibly unbounded, dimension.
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2011
This chapter discusses the most widely used regression models in competing risks. Following an introduction in Section 5.1, Section 5.2 discusses proportional cause-specific hazards models, and Section 5.3 discusses the proportional subdistribution hazards model. The cause-specific hazards are as defined in Chapter 3.
Jan Beyersmann +2 more
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This chapter discusses the most widely used regression models in competing risks. Following an introduction in Section 5.1, Section 5.2 discusses proportional cause-specific hazards models, and Section 5.3 discusses the proportional subdistribution hazards model. The cause-specific hazards are as defined in Chapter 3.
Jan Beyersmann +2 more
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Mixtures of proportional hazards regression models
Statistics in Medicine, 1999This paper presents a mixture model which combines features of the usual Cox proportional hazards model with those of a class of models, known as mixtures-of-experts. The resulting model is more flexible than the usual Cox model in the sense that the log hazard ratio is allowed to vary non-linearly as a function of the covariates.
O, Rosen, M, Tanner
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Model misspecification in proportional hazards regression
Biometrika, 1995Summary: The proportional hazards model is frequently used to evaluate the effect of treatment on failure time events in randomised clinical trials. Concomitant variables are usually available and may be considered for use in the primary analyses under the assumption that incorporating them may reduce bias or improve efficiency.
Anderson, Garnet L., Fleming, Thomas R.
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Non-proportional hazards models
2021The most general model, described in Chapter 4 covers a very broad spread of possibilities and, in this chapter, we consider some special cases.
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The Proportional Hazards Model
1988In this chapter and Chapter 7, we will consider models of the length of time until recidivism that contain individual characteristics as explanatory variables. The models of Chapter 7 will be parametric models in the sense that they will assume a particular distribution for the survival times; for example, we will estimate a model based on the ...
Peter Schmidt, Ann Dryden Witte
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Proportional transition hazards models
2011As with competing risks, the most widely used regression model for multistate data assumes a proportional hazards form for the transition hazards of the multistate model. We re-emphasize that the proportional hazards assumption is made for interpretational and technical convenience. As in Chapter 9, we consider n individuals under study with individual
Jan Beyersmann +2 more
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