Results 241 to 250 of about 328,188 (291)
Some of the next articles are maybe not open access.
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.
openaire +2 more sources
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.
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
Proportional hazards model with random effects
Statistics in Medicine, 2000We propose a general proportional hazards model with random effects for handling clustered survival data. This generalizes the usual frailty model by allowing a multivariate random effect with arbitrary design matrix in the log relative risk, in a way similar to the modelling of random effects in linear, generalized linear and non-linear mixed models ...
F, Vaida, R, Xu
openaire +2 more sources
Visualizing covariates in proportional hazards model
Statistics in Medicine, 2009AbstractWe present a graphical method called the rank‐hazard plot that visualizes the relative importance of covariates in a proportional hazards model. The key idea is to rank the covariate values and plot the relative hazard as a function of ranks scaled to interval [0, 1].
Juha, Karvanen, Frank E, Harrell
openaire +2 more sources
Conditional Proportional Hazards Models
1996Bivariate survival models can sometimes be characterized in terms of conditional survival functions of the form P(X > x|Y > y) and P(Y > y|X > x). Attention is focussed on models in which these conditional survival functions are of the proportional hazards form.
Barry C. Arnold, Yong Hee Kim
openaire +1 more source
Frailty models that yield proportional hazards
Statistics & Probability Letters, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Aalen, Odd O., Hjort, Nils Lid
openaire +2 more sources
Discrete Proportional Hazards Models for Mismeasured Outcomes
Biometrics, 2003Outcome mismeasurement can lead to biased estimation in several contexts. Magder and Hughes (1997, American Journal of Epidemiology 146, 195-203) showed that failure to adjust for imperfect outcome measures in logistic regression analysis can conservatively bias estimation of covariate effects, even when the mismeasurement rate is the same across ...
Meier, Amalia S. +2 more
openaire +3 more sources
Masking Unmasked in the Proportional Hazards Model
Biometrics, 2000Summary.Influence measures based on the pairwise deletion approach and the differentiation approach are developed for unmasking observations masked by other observations in the proportional hazards model. These influential observations might have substantial impact on statistical inference and might provide important information for model adequacy. One
Wei, Wen Hsiang, Kosorok, Michael R.
openaire +3 more sources