Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete hazard function and the time-dependent parameters, two estimation methods have been used that depend on the Bayes method according to dynamic modeling: the Maximum A Posterior method (MAP) This method was done using numerical methods represented by a Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation maximization algorithm (EM), the other method is represented by the Hybrid Markov Chains Monte Carlo (HMCMC) method using the Metropolis Hasting algorithm (MH) and Gypsum sampling (GS). It was concluded that survival analysis by descretization the data into a set of intervals is more flexible and fluid, as this allows analyzing risks and diagnosing impacts that vary over time. The study was applied in the survival analysis on dialysis until either death occurred due to kidney failure or the competing event, represented by kidney transplantation. The most important variables affecting the patient’s cessation of dialysis were also identified for both events in this research.
Abstract:
The problem of poverty is one of the most important development challenges facing developing countries including Sudan for several decades. Although many efforts have been made to reduce poverty, however, its rates are increasing, and public policies adopted by the government in this regard remain elusive in achievinging its main objectives or making any significant progress. The purpose of the present study is to analyse poverty in Sudan by identifying its measurement, causes and the factors that have contributed to the increasing poverty rates over the past two decades. Also this study aims at investigating the interim poverty reduction strategy in Sudan as well as evaluates that strategy throug
... Show MoreIn this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th
... Show MoreChemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi
... Show MoreThe current study was designed to compare some of the vital markers in the sera of diabetic and neuropathy patients via estimating Adipsin, Fasting blood Glucose(FBG), Glycated(HbA1c) hemoglobin, Homeostasis Model Assessment Index (Homa IR ), Cholesterol, High density lipoprotein (HDL), Triglycerides (T.G), Low-density, and lipoprotein (LDL), Very Low Density Lipoprotein (VLDL), in sera of Iraqi patients with diabetes and neuropathy. A total of ninety subjects were divided into three groups: group I (30 diabetic with neuropathy males) and group II (30 diabetic males without neuropathy), and 30 healthy sujects were employed as control group. The results showed a significant decline in Adipsin levels (p>0.05) in neuropathy, T2DM g
... Show MoreThe research aims to design an electronic program that allows users to assess the possibility of different practices for projects management professional according to the PMBOK methodology)) and using the requirements Data mentioned in the "knowledge and experience in project management Evaluation guide" issued by the professional Institute of project management According to the results of this program will be electronic The possible classification of project management in terms of both (proficiency_ perform tasks) as less than the desired level or within or above average in terms of best practices, and finally a number of recommendations to overcome the possible shortcomings. The most important is the need to enrich the service
... Show MoreThe aim of this study is to assess nurse's knowledge and role in the management of thalassemic patients in the Sulaimania Thalassemia Centre. Methodology: This study utilized a qualitative approach to explore nurses’ knowledge about thalassemia through semi structured group interviews. Questionnaire was synthesized through a comprehensive review of literature. Results: The results show that nurses in Kurdistan region of Iraq have a limited role in terms of decision making and there is lack of nursing documentation other than that of recording abnormal events, and a lack of knowledge about and engageme
This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.
ABSTRACT
Agricultural production, food security and safety, public health animal welfare, access to markets and alleviation of rural poverty have been achieved by controlling on veterinary services to prevent animal disease. World organization for animal health guidelines focus on controlling of animal disease which depends on good governance and veterinary services quality. The aim of veterinary services is controlling and preventing animal disease some of other aspects; it's responsibility of early detection, rapid response to outbreaks of emerging or re-emerging animal disease, optimizing quality and effectiveness of disease
... Show MoreThe research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests
... Show MoreMethods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and
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