The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations
Because of the tremendous changes in the business environment and significant growth in living standards, increased demand for services in general and about the realized practitioners in the field of service that traditional marketing strategies and models administrative based solutions to mono as the price alone does not lead to the desired outcomes with customers and even organizations as it does not apply always for the manufacture of their services unique . therefore , the need to learn marketing service order and a clear and critical to avoid failures in service and the marketing document to knowledge would avoid the organization that the failure in the delivery of service and enhances the desired response to fix it in a tim
... Show MoreThis study was conducted in Diyala province for renal failure patients during the periods August 2015 - April 2016. Hundred renal failure patients were enrolled in the study after diagnosis by the consultant physician at Ibn-Sina Center for Dialysis in Baquba Teaching Hospital according to criteria adopted by the World Health Organization for diagnosis of renal failure disease. The number of males in patient’s sample was 61 (61%) and females was 39 (39%) with an age range of 10 – 88 year (44.7 ± 22.1 year). In addition, the study included 50 apparently healthy individuals and considered as a group control, in which the number of males and females was similar (25 individual), with an age range of 18 – 88 year (51.7 ± 17.3 year). The
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In view of the fact that high blood pressure is one of the serious human diseases that a person can get without having to feel them, which is caused by many reasons therefore it became necessary to do research in this subject and to express these many factors by specific causes through studying it using (factor analysis).
So the researcher got to the five factors that explains only 71% of the total variation in this phenomenon is the subject of the research, where ((overweight)) and ((alcohol in abundance)) and ((smoking)) and ((lack of exercise)) are the reasons that influential the most in the incidence of this disease.
Renal failure is a disease of the kidney, in which the renal excretory function is failed to process due to depression of the GFR. Renal failure is divided into acute and chronic depending on the period of the disease. The study was designed to investigate the level of oxidative stress in RF patients. Seventy-five subjects had enrolled in the study, who divided into three groups equally, in which they are healthy control, ARF patients, and CRF patients. The results had shown a significant
This study included a group of (15) chronic renal failure patients (CRF), an addition group of (15) healthy individual was concluded in this study for control. Trace and essential elements ( Zn, Cu , Ca , K , Na) were measured by atomic absorption and flam analyzer in sera of CRF patients pre and post dialysis and control groups. The results showed a significant ( p < 0.05) increase in Zn and k+ concentration in sera of CRF patients pre and post dialysis compared to the control group. While there is a significant decrease for copper concentration in sera of CRF patients pre and post dialysis compared to the control group. There was no significant alte
... Show MoreThe objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association
... Show MoreIn this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade
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Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
... Show MoreThe logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
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