The Experts below are selected from a list of 300 Experts worldwide ranked by ideXlab platform
Florin Vaida - One of the best experts on this subject based on the ideXlab platform.
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Proportional Hazards Model with random effects
Statistics in Medicine, 2000Co-Authors: Florin VaidaAbstract:We 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. The distribution of the random effects is generally assumed to be multivariate normal, but other (preferably symmetrical) distributions are also possible. Maximum likelihood estimates of the regression parameters, the variance components and the baseline hazard function are obtained via the EM algorithm. The E-step of the algorithm involves computation of the conditional expectations of functions of the random effects, for which we use Markov chain Monte Carlo (MCMC) methods. Approximate variances of the estimates are computed by Louis' formula, and posterior expectations and variances of the individual random effects can be obtained as a by-product of the estimation. The inference procedure is exemplified on two data sets.
Torben Martinussen - One of the best experts on this subject based on the ideXlab platform.
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on estimation and tests of time varying effects in the Proportional Hazards Model
Scandinavian Journal of Statistics, 2004Co-Authors: Thomas H Scheike, Torben MartinussenAbstract:. Cox's Proportional Hazards Model is routinely used in many applied fields, some times, however, with too little emphasis on the fit of the Model. In this paper, we suggest some new tests for investigating whether or not covariate effects vary with time. These tests are a natural and integrated part of an extended version of the Cox Model. An important new feature of the suggested test is that time constancy for a specific covariate is examined in a Model, where some effects of other covariates are allowed to vary with time and some are constant; thus making successive testing of time-dependency possible. The proposed techniques are illustrated with the well-known Mayo liver disease data, and a small simulation study investigates the finite sample properties of the tests.
K. D. C. Stoodley - One of the best experts on this subject based on the ideXlab platform.
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Using the Proportional Hazards Model to study heart valve replacement data.
Medical informatics = Medecine et informatique, 1992Co-Authors: Brian D. Bunday, V. A. Kiri, K. D. C. StoodleyAbstract:The Proportional Hazards Model is used to study the effect of various concomitant variables on the time to valve failure, mortality, or other complications, for patients who have had artificial heart valves inserted. The data are from a database, which is still being assembled as more information is acquired, at Killingbeck Hospital. A suite of computer programs, not specifically developed with this application in mind, has been used to carry out the exploratory data analysis, the estimation of parameters and the validation of the Model. These three elements of the analysis are all illustrated. The present report is seen as a preliminary study to assess the usefulness of the Proportional Hazards Model in this area. Follow-up work as more data are accumulated is intended.
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The Reliability of Artificial Heart Valves ‐ A Case Study for the Proportional Hazards Model
International Journal of Quality & Reliability Management, 1992Co-Authors: Brian D. Bunday, V. A. Kiri, K. D. C. StoodleyAbstract:Investigates the medical factors affecting the reliability of artificial heart valves using the Proportional Hazards Model. The data, from a database which is still being assembled at Killingbeck Hospital, Leeds, refer to patients who have had artificial heart valves implanted. The analysis of the data has been carried out using a suite of programs not specifically designed with this application in mind. Illustrates the exploratory analysis, the parameter estimation for the Model and the validation of the Model, being a preliminary study to assess the value of the Proportional Hazards Model for this area. Follow‐up work, as the database is revised and augmented, is intended.
Dhananjay Kumar - One of the best experts on this subject based on the ideXlab platform.
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Proportional Hazards Model — AN APPLICATION TO POWER SUPPLY CABLES OF ELECTRIC MINE LOADERS
International Journal of Reliability Quality and Safety Engineering, 1994Co-Authors: Dhananjay Kumar, Bengt KlefsjöAbstract:The electric power supply cable is one of the most critical components of an electric mine loader. The effects of operating conditions such as fault types, cable types, numbers and types of repair done, the machines on which these cables are used, are analyzed using the Proportional Hazards Model. The relatively important operating conditions influencing the life length of the cable are identified and their magnitudes are estimated. Before fitting any Model to the data, simple graphical tools have been used in formulating covariates and selecting the suitable Model. The Proportional Hazards Model is found to be an effective tool for analyzing the effects of covariates. Graphical methods have been used to test the goodness-of-fit of the Proportional Hazards Model.
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Proportional Hazards Model: a review
Reliability Engineering & System Safety, 1994Co-Authors: Dhananjay Kumar, Bengt KlefsjöAbstract:Abstract The Proportional Hazards Model was introduced in 1972 by D. R. Cox in order to estimate the effects of different covariates influencing the times to the failures of a system. The Model has been used rather extensively in biomedicine and, recently, interest in its application in reliability engineering has increased. The main purpose of this expository paper is to review the existing literature on the Proportional Hazards Model. At first, the characteristics of the method are explained and its importance in reliability analysis is presented. Subsequently, methods for estimating parameters, along with the small and large sample properties of the estimators, are briefly discussed. Afterwards, work carried out so far on topics such as the effects of interaction, omission, measurement error, misclassification, monotonicity, multicolinearity and time dependency of covariates on the estimator are summarized. Some goodness-of-fit tests, especially those based on graphical methods, are described. We also describe some possible extensions of this Model considered so far and available computer programs and packages for estimating the parameters of this Model. Finally, some areas for further research are also discussed.
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Reliability analysis of power transmission cables of electric mine loaders using the Proportional Hazards Model
Reliability Engineering and System Safety, 1992Co-Authors: Dhananjay Kumar, Bengt Klefsjö, Uday KumarAbstract:The Proportional Hazards Model (PHM) is a powerful technique which can be used to investigate the effects of operating environment and the diagnostic variables (covariates) associated with an item on its life length. In this paper the effects of two different designs and maintenance on the reliability of a power transmission cable of an electric mine loader is investigated using PHM. The purpose of the paper is to illustrate the application of this Model in making decisions about selecting the proper material or the design of an item to meet the required purpose efficiently. © 1992.
Thomas H Scheike - One of the best experts on this subject based on the ideXlab platform.
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on estimation and tests of time varying effects in the Proportional Hazards Model
Scandinavian Journal of Statistics, 2004Co-Authors: Thomas H Scheike, Torben MartinussenAbstract:. Cox's Proportional Hazards Model is routinely used in many applied fields, some times, however, with too little emphasis on the fit of the Model. In this paper, we suggest some new tests for investigating whether or not covariate effects vary with time. These tests are a natural and integrated part of an extended version of the Cox Model. An important new feature of the suggested test is that time constancy for a specific covariate is examined in a Model, where some effects of other covariates are allowed to vary with time and some are constant; thus making successive testing of time-dependency possible. The proposed techniques are illustrated with the well-known Mayo liver disease data, and a small simulation study investigates the finite sample properties of the tests.
