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21.
AbstractFrailty models are used in survival analysis to account for unobserved heterogeneity in individual risks to disease and death. To analyze bivariate data on related survival times (e.g., matched pairs experiments, twin, or family data), shared frailty models were suggested. Shared frailty models are frequently used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of random factor(frailty) and baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and distribution of frailty. In this paper, we introduce shared gamma frailty models with reversed hazard rate. We introduce Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. Also, we apply the proposed model to the Australian twin data set. 相似文献
22.
ABSTRACTThe shared frailty models are often used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of a random factor (frailty) and the baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and the distribution of frailty. In this paper, we consider inverse Gaussian distribution as frailty distribution and three different baseline distributions, namely the generalized Rayleigh, the weighted exponential, and the extended Weibull distributions. With these three baseline distributions, we propose three different inverse Gaussian shared frailty models. We also compare these models with the models where the above-mentioned distributions are considered without frailty. We develop the Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. A search of the literature suggests that currently no work has been done for these three baseline distributions with a shared inverse Gaussian frailty so far. We also apply these three models by using a real-life bivariate survival data set of McGilchrist and Aisbett (1991) related to the kidney infection data and a better model is suggested for the data using the Bayesian model selection criteria. 相似文献
23.
《统计学通讯:模拟与计算》2013,42(3):581-595
This paper concerns maximum likelihood estimation for the semiparametric shared gamma frailty model; that is the Cox proportional hazards model with the hazard function multiplied by a gamma random variable with mean 1 and variance θ. A hybrid ML-EM algorithm is applied to 26 400 simulated samples of 400 to 8000 observations with Weibull hazards. The hybrid algorithm is much faster than the standard EM algorithm, faster than standard direct maximum likelihood (ML, Newton Raphson) for large samples, and gives almost identical results to the penalised likelihood method in S-PLUS 2000. When the true value θ0 of θ is zero, the estimates of θ are asymptotically distributed as a 50–50 mixture between a point mass at zero and a normal random variable on the positive axis. When θ0 > 0, the asymptotic distribution is normal. However, for small samples, simulations suggest that the estimates of θ are approximately distributed as an x ? (100 ? x)% mixture, 0 ≤ x ≤ 50, between a point mass at zero and a normal random variable on the positive axis even for θ0 > 0. In light of this, p-values and confidence intervals need to be adjusted accordingly. We indicate an approximate method for carrying out the adjustment. 相似文献
24.
This paper deals with the analysis of multivariate survival data from a Bayesian perspective using Markov-chain Monte Carlo methods. The Metropolis along with the Gibbs algorithm is used to calculate some of the marginal posterior distributions. A multivariate survival model is proposed, since survival times within the same group are correlated as a consequence of a frailty random block effect. The conditional proportional-hazards model of Clayton and Cuzick is used with a martingale structured prior process (Arjas and Gasbarra) for the discretized baseline hazard. Besides the calculation of the marginal posterior distributions of the parameters of interest, this paper presents some Bayesian EDA diagnostic techniques to detect model adequacy. The methodology is exemplified with kidney infection data where the times to infections within the same patients are expected to be correlated. 相似文献
25.
Shola Adeyemi Thierry J. Chaussalet Haifeng Xie Md Asaduzaman 《Journal of applied statistics》2010,37(4):691-701
Patient flow modeling is a growing field of interest in health services research. Several techniques have been applied to model movement of patients within and between health-care facilities. However, individual patient experience during the delivery of care has always been overlooked. In this work, a random effects model is introduced to patient flow modeling and applied to a London Hospital Neonatal unit data. In particular, a random effects multinomial logit model is used to capture individual patient trajectories in the process of care with patient frailties modeled as random effects. Intuitively, both operational and clinical patient flow are modeled, the former being physical and the latter latent. Two variants of the model are proposed, one based on mere patient pathways and the other based on patient characteristics. Our technique could identify interesting pathways such as those that result in high probability of death (survival), pathways incurring the least (highest) cost of care or pathways with the least (highest) length of stay. Patient-specific discharge probabilities from the health care system could also be predicted. These are of interest to health-care managers in planning the scarce resources needed to run health-care institutions. 相似文献
26.
社区应急管理是区域应急体系中的重要组成部分。社区应急管理的基础工作是明晰应急管理中的薄弱环节,采取有效的针对性措施,提高预防与应急能力。文章利用模糊综合评价方法,从人口社会特征、政治与经济、地理与环境、公共管理等四个方面,探讨了影响城市社区应急管理的脆弱性因子,分析了城市社区应急管理脆弱性的识别,为制定有效应急预案提供参考。 相似文献
27.
Quincy Thomas Stewart 《Mathematical Population Studies》2013,20(1):51-72
Brass' relational model is based on a linear relationship between the logits of the cumulative probability of dying before age x in a standard mortality distribution and those observed in any population. In this study the appropriate way to estimate the linear parameters associated with Brass' model is clarified. Five methods are presented to estimate the coefficients associated with Brass' relational model. Each method is applied to simulated data to examine the efficiencies of each model in mortality estimation. 相似文献
28.
The p -variate Burr distribution has been derived, developed, discussed and deployed by various authors. In this paper a score statistic for testing independence of the components, equivalent to testing for p independent Weibull against a p -variate Burr alternative, is obtained. Its null and non-null properties are investigated with and without nuisance parameters and including the possibility of censoring. Two applications to real data are described. The test is also discussed in the context of other Weibull mixture models. 相似文献
29.
Sahu Sujit K. Dey Dipak K. Aslanidou Helen Sinha Debajyoti 《Lifetime data analysis》1997,3(2):123-137
Frequently in the analysis of survival data, survival times within the same group are correlated due to unobserved co-variates.
One way these co-variates can be included in the model is as frailties. These frailty random block effects generate dependency
between the survival times of the individuals which are conditionally independent given the frailty. Using a conditional proportional
hazards model, in conjunction with the frailty, a whole new family of models is introduced. By considering a gamma frailty
model, often the issue is to find an appropriate model for the baseline hazard function. In this paper a flexible baseline
hazard model based on a correlated prior process is proposed and is compared with a standard Weibull model. Several model
diagnostics methods are developed and model comparison is made using recently developed Bayesian model selection criteria.
The above methodologies are applied to the McGilchrist and Aisbett (1991) kidney infection data and the analysis is performed
using Markov Chain Monte Carlo methods.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
30.
Alan C. Kimber 《Lifetime data analysis》1996,2(1):63-71
The Weibull distribution is a natural starting point in the modelling of failure times in reliability, material strength data and many other applications that involve lifetime data. In recent years there has been a growing interest in modelling heterogeneity within this context. A natural approach is to consider a mixture, either discrete or continuous, of Weibull distributions. A judicious choice of mixing distribution yields a tractable and flexible generalization of the Weibull distribution. In this note a score test for detecting heterogeneity in this context is discussed and illustrated using some infant nutrition data. 相似文献