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Binary Logistic Regression Analysis of Identifying Demographic, Socioeconomic, and Cultural Factors that Affect Fertility Among Women of Child bearing Age in Ethiopia
Issue:
Volume 6, Issue 3, June 2018
Pages:
65-73
Received:
26 March 2018
Accepted:
12 April 2018
Published:
1 June 2018
Abstract: Fertility is one of the elements in population dynamics that has a significant contribution towards changing population size and structure overtime. The aim of objective of this study is to identify Demographic, Socio-economic, and Cultural factors that affect Fertility level among women of childbearing age in Ethiopia. The data for this study were taken from Ethiopia Demographic and Health Survey conducted in 2011 (EDHS2011). For modelling purpose binary logistic regression was used and data were analyzed using SPSS Version16. The total number of women in childbearing age is based on10,897 women who have at least one child and whose age ranges from15 to 49 years. Among these, 8130 (74.6%) reside in rural areas where as 2767 (25.4%) reside in urban hubs. Among those individuals 64.2% were currently not working and the remaining 35.8% of the respondent were categorized under currently working group. In relation to age at first Cohabitation, about 37.7% of individuals were fail under 15-17 interval of age category and 34.5% of respondent were greater than or equal to 18 years old. The majority of individuals were married 8621 (79.1%), followed by divorced and living with partner (716 (6.6%) and living with partner 588 (5.4%) respectively). In the analyses, all the variables Region, women educational level, wealth index, husband’s/partner’s educational level, marital status, age at first cohabitation and age in 5-years group were found to have significant effect on total number of child ever born at significance level of 5%. From the fitted logistic regression model, the estimates odds ratio displayed in table 5, for the variable region reference category is Addis Ababa. The value of the odds ratio 
for region that the odds of having TCEB greater than or equals to five children for Tigray region is have 38.4% more than those individuals in Addis Ababa (OR=1.384, C.I=1.055-1.810) and its effect is statistically significant.
Abstract: Fertility is one of the elements in population dynamics that has a significant contribution towards changing population size and structure overtime. The aim of objective of this study is to identify Demographic, Socio-economic, and Cultural factors that affect Fertility level among women of childbearing age in Ethiopia. The data for this study were...
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Computer Simulation-Based Designs for Industrial Engineering Experiments
Dongyu Zhou,
Weihua Guo,
Hengzhen Huang
Issue:
Volume 6, Issue 3, June 2018
Pages:
74-80
Received:
27 April 2018
Accepted:
19 May 2018
Published:
7 June 2018
Abstract: Computer simulations have been receiving a lot of attention in industrial engineering as the rapid growth in computer power and numerical techniques. In contrast to physical experiments which are usually carried out in factories, laboratories or fields, computer simulations can save considerable time and cost. From the statistical perspective, the current research work about computer simulations is mostly focusing on modeling the relationship between the output variable from the simulator and the input variables set by the experimenter. However, an experimental design with careful selection of the values of the input variables can significantly affect the quality of the statistical model. Specifically, prediction on the edge area of the experimental domain, which is extremely critical for an industrial engineering experiment often suffers from inadequate data information because the design points usually do not well cover the edge area of the experimental domain. To address this issue, a new type of design, called semi-LHD is proposed in this paper. Such a design type has the following appealing properties: (1) it encompasses a Latin hypercube design as a sub-design so that the design points are uniformly scattered over the interior of the design region; and (2) it possesses some extra marginal design points which are close to the edge so that the prediction accuracy on the edge area of the experimental domain is fully taken into account. Detailed algorithms for finding the marginal design points and how to construct the proposed semi-LHDs are given. Numerical comparisons between the proposed semi-LHDs with the commonly-used Latin hypercube designs, in terms of prediction accuracy, are illustrated through simulation studies. It turns out that the proposed semi-LHDs yield desirable prediction accuracy not only in the interior but also on the edge area of the experimental domain, so they are recommended as the experimental designs for simulation-based industrial engineering experiments.
Abstract: Computer simulations have been receiving a lot of attention in industrial engineering as the rapid growth in computer power and numerical techniques. In contrast to physical experiments which are usually carried out in factories, laboratories or fields, computer simulations can save considerable time and cost. From the statistical perspective, the ...
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The Mutual Nearest Neighbor Method in Functional Nonparametric Regression
Issue:
Volume 6, Issue 3, June 2018
Pages:
81-89
Received:
18 July 2018
Published:
19 July 2018
Abstract: In recent decades, functional data have become a commonly encountered type of data. Its ideal units of observation are functions defined on some continuous domain and the observed data are sampled on a discrete grid. An important problem in functional data analysis is how to fit regression models with scalar responses and functional predictors (scalar-on-function regression). This paper focuses on the nonparametric approaches to this problem. First there is a review of the classical k-nearest neighbors (kNN) method for functional regression. Then the mutual nearest neighbors (MNN) method, which is a variant of kNN method, is applied to functional regression. Compared with the classical kNN approach, the MNN method takes use of the concept of mutual nearest neighbors to construct regression model and the pseudo nearest neighbors will not be taken into account during the prediction process. In addition, any nonparametric method in the functional data cases is affected by the curse of infinite dimensionality. To prevent this curse, it is legitimate to measure the proximity between two curves via a semi-metric. The effectiveness of MNN method is illustrated by comparing the predictive power of MNN method with kNN method first on the simulated datasets and then on a real chemometrical example. The comparative experimental analyses show that MNN method preserves the main merits inherent in kNN method and achieves better performances with proper proximity measures.
Abstract: In recent decades, functional data have become a commonly encountered type of data. Its ideal units of observation are functions defined on some continuous domain and the observed data are sampled on a discrete grid. An important problem in functional data analysis is how to fit regression models with scalar responses and functional predictors (sca...
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Determination of Optimal Public Debt Ceiling for Kenya Using Stochastic Control
Millicent Kithinji,
Lucy Muthoni
Issue:
Volume 6, Issue 3, June 2018
Pages:
90-98
Received:
13 May 2018
Accepted:
19 June 2018
Published:
23 July 2018
Abstract: Public debt is a key economic variable. It is the totality of public and publicly guaranteed debt owed by any level of government to either citizens or foreigners or both. Due to recent debt crises in countries such as Portugal, Italy, Ireland, Greece and Spain, debt control has become a key important fiscal policy of every government. In this study, we applied a Public debt ceiling explicit formula to find out the optimal public debt ceiling for Kenya [3]. We made modification to subjective variables in the explicit formula and used the formula to find the optimal public debt ceiling for Kenya. We illustrate that it is prudent for that government to use a fiscal policy that maintains the debt ratio under an optimal debt ceiling.
Abstract: Public debt is a key economic variable. It is the totality of public and publicly guaranteed debt owed by any level of government to either citizens or foreigners or both. Due to recent debt crises in countries such as Portugal, Italy, Ireland, Greece and Spain, debt control has become a key important fiscal policy of every government. In this stud...
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Application of Factor Analysis in the Assessment of Solid Waste Management in Bolgatanga Municipality of Ghana
Edward Akurugu,
Abdul-Majeed Issahaku,
Abdul-Samed Aliou
Issue:
Volume 6, Issue 3, June 2018
Pages:
99-109
Received:
27 June 2018
Accepted:
9 July 2018
Published:
6 August 2018
Abstract: The issue of waste management has become a daunting challenge for many countries particularly for developing countries. The adverse effects of waste on human lives and the environment have reached scary levels that call for a thorough assessment of waste management systems across the globe and in particular developing countries. In Bolgatanga municipality of the Upper East Region of Ghana, the situation of waste disposal is appalling exposing residents to all kinds of health related risk. City authorities who have the responsibility of ensuring that the environment is clean and safe for habitation are confronted with the serious burden of managing waste disposal in the municipality. This study therefore sought to examine a set of 18 variables relevant to the topic under investigation and how they relate to influence solid waste management in the municipality from the perspective of residents of the Bolgatanga municipality through the application of Factor Analysis. The object of this approach is to identify a set of indicator variables that amalgamate to form common factors. The opinions of 400 subjects on Solid Waste Management in the municipality were successfully collected through the administration of questionnaires and analyzed. A preliminary analysis of the data showed that the correlation matrix was not an identity matrix and a KMO value of 0.797 described as “middling” was obtained. These provided the necessary and sufficient grounds for the application of Factor Analysis to the data. Further analysis of the data revealed five latent factors which are Institutional Dormancy, Financial Constraint, Infrastructural Lapses, Accessibility and Behavioral Canker as factors that need to be addressed in order to improve the status of Solid Waste Management in Bolgatanga municipality.
Abstract: The issue of waste management has become a daunting challenge for many countries particularly for developing countries. The adverse effects of waste on human lives and the environment have reached scary levels that call for a thorough assessment of waste management systems across the globe and in particular developing countries. In Bolgatanga munic...
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