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Modelling Time to Mortality with Congestive Heart Failure: A Case Study in Wollo General and Referral Government Hospitals
Habtamu Dessie,
Yenefenta Wube,
Belete Adelo,
Eskeziaw Abebe
Issue:
Volume 9, Issue 3, May 2020
Pages:
21-36
Received:
7 October 2019
Accepted:
16 April 2020
Published:
28 April 2020
Abstract: Congestive heart failure is a complex clinical syndrome of functional or structural impairment in the heart. Nowadays heart failure is common and increasing in the world and researches on this area is limited. Therefore the aim of the present study was to analyze and quantify the impact of modelling heart failure survival allowing for covariates with time varying effects known to be independent predictors of overall mortality in this clinical setting. A retrospective cohort study was conducted on CHF patients who were on treatment follow up at both WGH and DRH from January 1, 2010 to December 30, 2016. A total of 487 patients were selected by using simple random sampling from the patient's medical record. Semi parametric, parametric PH models and AFT models was employed to identify the best model which shown as the real causation of factors with the outcome of CHF which is death. The Weibull accelerated failure time model result showed that the risk factors related to accelerating or decelerating the lifespan were age (TR=0.962, p=0.000), Residence (rural) (TR=1.24, p=0.019), Nutritional (Poor) (TR=0.582, p=0.000), Smoking (TR=0.774, p=0.005), Alcoholism (TR=1.394, p=0.010), Diabetes mellitus (TR=0.49, p=0.000), Hypertension (TR=0.079, p=0.019), Stroke (TR=0.799, p=0.014), Coronary Artery disease (TR=0.276, p=0.012), Tuberculosis bacillus (TR=0.103, p=0.000) as a co morbidity and the interaction between age and Tuberculosis bacillus (p=0.000), age and Coronary artery disease (p=0.041), Diabetes mellitus with Hypertension (p=0.000), Hypertension with Nutritional status (p=0.000) and age with time (p=0.000) were found statistically significant. The Weibull accelerated failure time model performed better explain the effect of predictors than other Cox and parametric PH models. Thus, researchers should use parametric AFT models to see regression varying effect covariates. Frequent monitoring and follow up of Patients with heart failure should be adopted.
Abstract: Congestive heart failure is a complex clinical syndrome of functional or structural impairment in the heart. Nowadays heart failure is common and increasing in the world and researches on this area is limited. Therefore the aim of the present study was to analyze and quantify the impact of modelling heart failure survival allowing for covariates wi...
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Ethiopian Economic Features and Changing Persistence: A Time Series Analysis
Issue:
Volume 9, Issue 3, May 2020
Pages:
37-46
Received:
15 October 2019
Accepted:
15 April 2020
Published:
28 April 2020
Abstract: Ethiopia was one of the countries least developed and it is among the countries in the bottom in the rank of GDP’s that UN lists. However, nowadays Ethiopia is one of the fastest growing economies in the world. In Ethiopia much effort has been made to build the national economy. Ethiopia has made significant strides towards becoming a middle income country by 2025. This paper provides an overview of Box-Jenkins model for temporal data. In this research we used time series analysis of some of Ethiopian economic features such as GDP, GDP growth rate and inflation rate. Box-Jenkins model was used to analyze 35-year data (1981-2015). GDP, GDP growth rate, and inflation rate were variables under the study to describe persistence change and to forecast future behaviors. We tried to find best model for description and predictive model for these series using different model selection tools. We compared different orders of Autoregressive Integrated Moving Average (ARIMA) using AIC, BIC and MSE to fit the observed data. The best from compared was ARIMA (2, 2, 2) for GDP, ARIMA (2, 1, 2) for GDP growth rate and ARIMA (1, 1, 1) for inflation rate. Since forecasting is important for many purposes, we forecast the series from best ARIMA models. Five year forecast showing that GDP is an increasing trend and the average forecast of GDP rates is showing an average of 10.028.
Abstract: Ethiopia was one of the countries least developed and it is among the countries in the bottom in the rank of GDP’s that UN lists. However, nowadays Ethiopia is one of the fastest growing economies in the world. In Ethiopia much effort has been made to build the national economy. Ethiopia has made significant strides towards becoming a middle income...
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Assessment of Farmers Perception to Soil Fertility Management in Kalisha District, Hadiya Zone, Southern Ethiopia
Girma Woldemichael,
Abebech Endashaw,
Abinet Tadesse,
Berhanu Achamo
Issue:
Volume 9, Issue 3, May 2020
Pages:
47-52
Received:
5 December 2019
Accepted:
20 April 2020
Published:
14 May 2020
Abstract: Soil is one of the natural resource and under high pressure that is increasing from year to year, resulting in poor fertility. The objective of this study was to assess the attitudes of farmer’s perception to soil fertility management practices. In order to achieve these objectives, random sampling methods was used to select respondents in the study area. The data was collected by using field observation, questionnaires and key informant discussion. The collected data were analyzed through descriptive statistics. The survey revealed that the factors that hinder farmers from using improved ways of soil fertility management practices are: labor problem 27.5%, economic problem 20%, lack of awareness and demographic factors 37.5%. In the Kalisha District, there are a number of major indigenous soil fertility management practices (SFMP) that are using by almost all farmers such as using cattle dung, straw, intercropping legumes crops in their farm land and use of enset in homegarden area. In other form, this study showed that, in Kalisha District the attitudes of farmers to soil fertility management is less, due to the awareness gap in society and less interventions of development agents. Therefore the farmers should be aware of soil fertility management practices on both biological and physical measures to restore soil fertility and they have to scale up the indigenous SFMP to maintain the productivity of the soil.
Abstract: Soil is one of the natural resource and under high pressure that is increasing from year to year, resulting in poor fertility. The objective of this study was to assess the attitudes of farmer’s perception to soil fertility management practices. In order to achieve these objectives, random sampling methods was used to select respondents in the stud...
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On the Application of Linear Discriminant Function to Evaluate Data on Diabetic Patients at the University of Port Harcourt Teaching Hospital, Rivers, Nigeria
Nicholas Pindar Dibal,
Christopher Akas Abraham
Issue:
Volume 9, Issue 3, May 2020
Pages:
53-56
Received:
16 April 2020
Accepted:
3 May 2020
Published:
18 May 2020
Abstract: Many real life events involves several interacting variables, hence multivariate statistical tool is necessary for appropriate analysis and interpretation. Discriminant analysis (DA) is one of the commonly used multivariate method in various fields of study including education, finance, environment, medicine etc., where complex data analysis and interpretation is required. This paper demonstrates and illustrate approaches in presenting how the discriminant analysis can be carried out on 335 (40 diabetics and 295 non-diabetic) patients and how the output can be interpreted using the Fisher’s linear Discriminant function (FLDF). The performance of FLDF was adjudged based on the percentage of correct reclassification of the original observation to yield the discriminant scores from the functions. Up to 65.4% correct classification was achieved, and similarly 62.7% percent of the cross-validated grouped cases were correctly classified into either being a Diabetic or non-diabetic patient. Patient’s age and gender were found to be the two most important contributing variables in classifying a patient between the two groups.
Abstract: Many real life events involves several interacting variables, hence multivariate statistical tool is necessary for appropriate analysis and interpretation. Discriminant analysis (DA) is one of the commonly used multivariate method in various fields of study including education, finance, environment, medicine etc., where complex data analysis and in...
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Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services
Richard Puurbalanta,
Mark Adjei,
Vida Afosaa
Issue:
Volume 9, Issue 3, May 2020
Pages:
57-62
Received:
18 November 2019
Accepted:
17 April 2020
Published:
27 May 2020
Abstract: The importance of improved healthcare services under Ghana’s National Health Insurance Scheme (NHIS) is nationwide admitted. However, service improvement for insurance schemes comes with extra cost. To fill the funding gap, insurance schemes typically charge enhanced premiums. This requires clients’ approval and cooperation to implement. For this reason, this study was conducted to assess Ghana’s NHIS subscribers’ willingness to pay (WTP) enhanced premiums for improved services. Some socio-economic and demographic factors were used as covariates. WTP, being the dependent variable, was categorized into high WTP, moderate WTP, low WTP, and no WTP enhanced premiums. The likelihood of a client falling in a particular WTP category was examined using the Cumulative Ordinal Probit (COP) regression model. A likelihood ratio chi-square of 58.82 with p < 0.000 shows that the model was statistically significant, and fit for prediction. Results showed that age-groups 18-30, 30–45, unemployed, tertiary education, and level of income significantly influenced WTP. Predictions showed that for any average national health insurance user, the probability of being in high WTP, moderate WTP, low WTP and no WTP premium are respectively 0.51, 0.27, 0.11 and 0.12. Based on the results of this study, we recommend that Ghana’s NHIS should institute a progressive premium regime in order to cater for the different needs and financial abilities of clients, thus helping to fill the funding gap.
Abstract: The importance of improved healthcare services under Ghana’s National Health Insurance Scheme (NHIS) is nationwide admitted. However, service improvement for insurance schemes comes with extra cost. To fill the funding gap, insurance schemes typically charge enhanced premiums. This requires clients’ approval and cooperation to implement. For this r...
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Examination of Covariance Structures for Experimental Design with Repeated Measure
Abraham Okolo,
Saidu Sauta Abdulkadir,
Ikeme John Dike,
Abubakar Adamu
Issue:
Volume 9, Issue 3, May 2020
Pages:
63-73
Received:
3 April 2020
Accepted:
3 May 2020
Published:
27 May 2020
Abstract: This research examine different covariance structures for experimental design with repeated measure data. Multiple responses taken sequentially from same experimental unit at different periods of time for quantitative data are referred as Repeated Measurement. Weight of 105 broilers in grams for six group obtained from jewel farm Gombe were used as research materials/data. Eleven different covariance structures including the modified one (UN, UNC, TOEP, TOEPH, ANTE(1), AR(1), ARH(1), CS, CSH, HF and ARFA(1)) were examined. AIC, AICC, BIC, HQIC, CAIC and the modified criteria ASIC were used to examine covariance structures and bring the best among them using the named information criteria. The result shows that sphericity assumptions was violated a such the best covariance structure was ARH(1) while the least structure was CSH. Also on the basis of goodness of fit criteria HQIC was found to be the best information criteria. When examined the best information criteria and covariance structure with the modified ones, the modified ASIC and ARFA(1) found to be the best. In conclusion examine different covariance structures with repeated measure data give a very good result defending on the kind of data.
Abstract: This research examine different covariance structures for experimental design with repeated measure data. Multiple responses taken sequentially from same experimental unit at different periods of time for quantitative data are referred as Repeated Measurement. Weight of 105 broilers in grams for six group obtained from jewel farm Gombe were used as...
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Impact of Treatment Parameter on Blood Flow in an Atherosclerotic Artery
Kubugha Wilcox Bunonyo,
Emeka Amos
Issue:
Volume 9, Issue 3, May 2020
Pages:
74-79
Received:
19 April 2020
Accepted:
7 May 2020
Published:
27 May 2020
Abstract: This research was carried out to investigate the impact of treatment parameter on blood flow in an atherosclerotic artery by formulating a momentum equation governing the flow in dimensional form which was scaled to dimensionless form using some important scaling parameters. The equation was solved analytical and obtained velocity profile, thereafter the volumetric flow rate, shear stress were calculated analytically and some pertinent physical parameters were obtained, finally Mathematica codes were developed to simulation the analytical results by varying the pertinent parameters to investigate the influence of the physical parameters on the blood flow profile, volumetric flow rate and the shear stress. In conclusion, it is seen that some of the pertinent parameters RT, Re, Da, M, ω, δ caused the flow to improve while the others did not, taken t=5 seconds. This research is very helpful in providing an insight of the treatment excessive intake of fatty substance.
Abstract: This research was carried out to investigate the impact of treatment parameter on blood flow in an atherosclerotic artery by formulating a momentum equation governing the flow in dimensional form which was scaled to dimensionless form using some important scaling parameters. The equation was solved analytical and obtained velocity profile, thereaft...
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