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On Local Linear Regression Estimation of Finite Population Totals in Model Based Surveys
Conlet Biketi Kikechi,
Richard Onyino Simwa,
Ganesh Prasad Pokhariyal
Issue:
Volume 7, Issue 3, May 2018
Pages:
92-101
Received:
10 February 2018
Accepted:
6 March 2018
Published:
24 March 2018
Abstract: In this paper, nonparametric regression is employed which provides an estimation of unknown finite population totals. A robust estimator of finite population totals in model based inference is constructed using the procedure of local linear regression. In particular, robustness properties of the proposed estimator are derived and a brief comparison between the performances of the derived estimator and some existing estimators is made in terms of bias, MSE and relative efficiency. Results indicate that the local linear regression estimator is more efficient and performing better than the Horvitz-Thompson and Dorfman estimators, regardless of whether the model is specified or mispecified. The local linear regression estimator also outperforms the linear regression estimator in all the populations except when the population is linear. The confidence intervals generated by the model based local linear regression method are much tighter than those generated by the design based Horvitz-Thompson method. Generally the model based approach outperforms the design based approach regardless of whether the underlying model is correctly specified or not but that effect decreases as the model variance increases.
Abstract: In this paper, nonparametric regression is employed which provides an estimation of unknown finite population totals. A robust estimator of finite population totals in model based inference is constructed using the procedure of local linear regression. In particular, robustness properties of the proposed estimator are derived and a brief comparison...
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Bayesian Dynamic Linear Regression Analysis of Infant Growth by Weight
Dereje Danbe Debeko,
Ayele Taye Goshu
Issue:
Volume 7, Issue 3, May 2018
Pages:
102-111
Received:
5 March 2018
Accepted:
19 March 2018
Published:
2 April 2018
Abstract: The most common anthropometric measurements used to assess physical growth patterns of infant from birth to one year period are body weight and length. Weight gain pattern is dynamic that could not be easily understood. The main objective of this study is to model the biological growth of infants by weight during the first year of their lives using the Bayesian hierarchical and dynamic linear regression model. The data used in this study was from a cohort study for infants born alive and followed from birth to one year period with six visits at Adare General Hospital. There has been a sample of 126 infants under follow-up from birth to 12 months old at Adare General Hospital, Hawassa Ethiopia. A total of 756 weight observations were collected from the following-up of the infants during the one year period. The Bayesian hierarchical and dynamic linear regression model was used to explore weight gain of infants incorporating individual and population level variations observed over time. The mean weight growth of the infants is found to be linearly increasing while variation was declining over the age. Rate of weight change of the infants had two optimum points that might represent inflection points of the growth at around six and eight months. Posterior distributions of the intercept and slope parameters were found to have normal distributions, from which important inferences about the infant’s growth can be derived. The Bayesian hierarchical and dynamic linear model can explain and capable to handle the weight growth patterns of the infants over the short period of time.
Abstract: The most common anthropometric measurements used to assess physical growth patterns of infant from birth to one year period are body weight and length. Weight gain pattern is dynamic that could not be easily understood. The main objective of this study is to model the biological growth of infants by weight during the first year of their lives using...
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A Simple Stochastic Stomach Cancer Model with Application
Josphat Mutwiri Ikiao,
Nyongesa Kennedy,
Robert Muriungi Gitunga
Issue:
Volume 7, Issue 3, May 2018
Pages:
112-117
Received:
3 December 2017
Accepted:
12 December 2017
Published:
11 April 2018
Abstract: Survival analysis majors mainly on estimation of time taken before an event of interest takes place. Time taken before an event of interest takes place is a random process that takes shape overtime. Stochastic processes theory is therefore very crucial in analysis of survival data. The study employed markov chain theory in developing a simple stochastic stomach cancer model. The model is depicted with a state diagram and a stochastic matrix. The model was applied to stomach cancer data obtained from Meru Hospice. Transition probability theory was used in determining transition probabilities. The entries of the stochastic matrix T were estimated using the Aalen-Johansen estimators. The time taken for all the people under the study to transit to death was estimated using the limiting matrix.
Abstract: Survival analysis majors mainly on estimation of time taken before an event of interest takes place. Time taken before an event of interest takes place is a random process that takes shape overtime. Stochastic processes theory is therefore very crucial in analysis of survival data. The study employed markov chain theory in developing a simple stoch...
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Correspondence Analysis as a Strategy to Explore the Association between Different Categories of Crime in Yobe State, Nigeria
Nicholas Pindar Dibal,
Ibrahim Adamu Usman
Issue:
Volume 7, Issue 3, May 2018
Pages:
118-125
Received:
22 February 2018
Accepted:
20 March 2018
Published:
13 April 2018
Abstract: With the rapid increase in population at both rural and urban areas and the increasing rate of unemployment, criminal activities in Nigeria have increased dramatically in dimension, frequency and sophistication. The study examine the relationships between crimes committed by criminals that were caught and reported to the police by individuals or apprehended by the police and their offences documented in police stations across Yobe State for the period of ten years using correspondence analysis. The crimes analyzed were; murder, robbery, rape, theft, house breaking, kidnapping, grievous hurt and wounding, assault, store breaking, fraud and cheating. The analyzed complex relationships between the different crimes and the local government areas showed significant relationships between the different categories of the variables. The gained information is useful in developing action plans for identified high-risk areas, building a strong database of habitual offenders and, building crime and intelligence database for national security, law enforcement agencies and the business community.
Abstract: With the rapid increase in population at both rural and urban areas and the increasing rate of unemployment, criminal activities in Nigeria have increased dramatically in dimension, frequency and sophistication. The study examine the relationships between crimes committed by criminals that were caught and reported to the police by individuals or ap...
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Investigating the Causes of Students’ Less Academic Performance in Engineering College of Debre Berhan University
Hiluf Reda,
Getahun Mulugeta
Issue:
Volume 7, Issue 3, May 2018
Pages:
126-131
Received:
22 March 2018
Accepted:
8 April 2018
Published:
28 April 2018
Abstract: Student success is a critical issue facing higher education today. Schools, colleges and universities have no worth without students. Students are most essential asset for any educational institute. Less academic performance of students in universities especially in engineering colleges and its ripple effects are looming dangers for Ethiopia. The main purpose of this research is to identify and examine factors that affect students’ academic performance at DBU College of engineering. To achieve this objective a sample of 263 students have taken and self-administered questionnaires were distributed through the selected respondents. Both descriptive and inferential statistics were employed. From the descriptive result of the study it has shown that the average CGPA of engineering student is 2.93 with minimum of 2.00 and maximum of 3.96. From multiple linear regression result it is evident that student interest, study habit and previous background factors have a significant effect on the academic performance of students. From the result of the study it is concluded that assigning departments based on the interest of students, effective study habit and good previous background enhances the performance of engineering students. And it is recommended that Orientation and special training should be given for fresh students about effective study habit at the very beginning of the academic year, a continuous and strategic work should be done on students at the lower grades in line with engineering departments in the university, assigning of departments should be conducted based on the interest of students and finally this research should be implemented as project work to enhance the performance of engineering students.
Abstract: Student success is a critical issue facing higher education today. Schools, colleges and universities have no worth without students. Students are most essential asset for any educational institute. Less academic performance of students in universities especially in engineering colleges and its ripple effects are looming dangers for Ethiopia. The m...
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