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Mediation analysis with causally ordered mediators using Cox proportional hazards model
Statistics in Medicine, 2018Causal mediation analysis aims to investigate the mechanism linking an exposure and an outcome. However, studies regarding mediation effects on survival outcomes are limited, particularly in multi‐mediator settings.
Shu-Hsien Cho, Yen-Tsung Huang
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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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Survival Analysis with Cox Proportional Hazards Model in Predicting Patient Outcomes
International Conference Electronic Systems, Signal Processing and Computing Technologies [ICESC-]Survival analysis is crucial for understanding the factors that influence patient outcomes across time. The objective is to predict the outcomes of patient survival under various circumstances using the Cox Proportional Hazards Model. The main objectives
Monikapreethi S K +5 more
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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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Regression analysis of bivariate current status data under the proportional hazards model
, 2017This article discusses the regression analysis of bivariate current status or case I interval‐censored failure time data under the marginal proportional hazards model.
T. Hu, Qingning Zhou, Jianguo Sun
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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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