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Abstract: Lindley Approximation Technique for the Parameters of Lomax Distribution
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Abstract: The present study is concerned with the estimation of shape and scale parameter of Lomax distribution using Bayesian approximation techniques (Lindley’s Approximation). Different priors viz gamma, exponential and Levy priors are used to obtain the Bayes estimates of parameters of Lomax distributions under Lindley approximation technique. For comparing the efficiency of the obtained results a simulation study is carried out using R-software. Keywords: Lomax distribution, Bayesian Estimation, Prior, Loss functions, Lindley’s Approximation. /td> |
Abstract: Effects of some Biological Covariates on the Probability of First Recurrence of Malaria following Treatment with Artemisinin Combination Therapy
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Abstract: Many investigations have shown that artemisinin-based combination therapies are effective in the treatment of uncomplicated malaria and that they do not increase parasite resistance to treatment as much as treatment with single substance. We study the relation between some biological covariates and the time to first recurrence of malaria for children treated for malaria in a clinical trial. One group received artesunate plus sulfadoxine-pyrimethamine and the other only sulfadoxine-pyrimethamine. We consider the event malaria-free for the first 42 (and 84) days. We use logistic regression models for the analyses. The main results show that the probability of no recurrence is higher if the parasite density in the blood is high. The results are inconclusive for other explanatory biological variables. The infecting parasites having genes that indicate resistance, gave different results at the two different treatment centres. There was no appreciable difference in the effects of treatment over the two follow-up periods and these treatments do not have any effect on the probability of a recurrence. Keywords: Logistic model, clinical covariates, malaria treatment, parasite density, drug resistance, genotype, incomplete data. |
Abstract: The Trend of the Bibliographical Output from Libyan Engineering Schools: A 30-Year Review From 1984-2013
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Abstract: In this study, the research output from the major Libyan engineering schools was gathered and compared for the period of thirty years (from 1984 to 2013). The Elsevier database, Science Direct, was used to gather these publications and only engineering articles were included. A comparative analysis was performed on three levels; first a local comparison between the different faculties of engineering across Libya and secondly, a broader comparison between Libya and the neighboring METAL (Morocco, Egypt, Tunisia, Algeria and Libya) countries and finally, the third comparison was performed between Turkey and the METAL countries. In the local comparison, the output was normalized by the number of teaching staff while in the broader regional comparison, gross domestic product and population were used as standardization factors. When analyzing the research output of the Libyan engineering schools, it was observed that most publications came from Tripoli (47.1%, n=131) followed by Benghazi (25.9%, n=72), Misurata (4.1%, n=12) and Omar Al-Mukhtar (4.0%, n=11). However, when the number of staff members was taken into consideration, Benghazi University and Omar Al-Mukhtar University had higher research productivity levels than Tripoli University and Misurata University respectively. The regional comparison showed a clear difference between Libya and its neighbors, having the lowest output among them. Finally, it was found that across the three decades under study, Turkey produced more research than all the METAL countries combined. More attention needs to be paid to research and publications in Libyan engineering schools. A number of recommendations were made to help improve the publication rate in Libyan engineering faculties. Keywords: Education, Statistics, Bibliography, Conflict studies. |
Abstract: Probability Sampling in Matched Case-Control Study in Drug Abuse
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Abstract: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases”. Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. Bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors when compared to the non-bootstrap analysis. Comparison of ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93 for random-sample data vs. 0.91 for snowball-sample data (p=0.35)); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p<.001). The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling. Keywords: Random sampling, bootstrapping, non-random sampling, ROC curve. |
