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Item Acceptance of biotechnology and social-cultural implications in Ghana(African Journal of Biotechnology, 2009-05) Quaye, W.; Yawson, I.; Yawson, R.M.; Williams, I.E.Despite major scientific progress in the application of biotechnology in agriculture, public attitudes towards biotechnology in general and genetically modified food (GM food) products in particular remain mixed in Africa. Examining responses on acceptance of GM food through a stakeholder survey in Ghana, it was established that half of the 100 people sample interviewed were not in favor of GM foods. To this group acceptance of GM foods would make farmers loose focus on the traditional ways of cultivation, putting the whole nation at the mercy of profit driven foreign companies who produce GM foods. In order to have clear and unbiased attitudes towards agricultural biotechnology in Africa, there is the need to substitute dominant ideologies in the way biotechnology research and dissemination are conducted in developed countries with tailor-made methodologies in developing countries. This paper emphasizes the social dynamic force of food focusing on the need for social shaping of biotechnologies to reflect local and regional needs. Respondents' perceptions of GM foods suggest that food is seen as not just a commodity to be consumed but food has both cultural and national identities. Generally, people are identified by their consumption and nutrition lifestyles and therefore take pride in what they eat. A proposal is made to set biotechnology research agenda in the context of social choices; social scientific coalition of biotechnology with endogenous development pathways' as opposed to 'exogenous biotechnology research'. Also there is the need for adequate capacity building of the existing regulatory institutions to handle ethical and moral issues associated with biotechnology research since survey findings showed lacked of public confidence in them. © 2009 Academic Journals.Item Large deviation principles for empirical measures of colored random graphs(Annals of Applied Probability 6(20): 1989-2021, 2010) Doku-Amponsah, K.; MÖrters, P.For any finite colored graph we define the empirical neighborhood measures, which counts the number of vertices of a given color connected to a given number of vertices of each color, and the empirical pair measure, which counts the number of edges connecting each pair of colors. For a class of models of sparse colored random graphs, we prove large deviation principles for these empirical measures In the weak topology. The rate functions governing our large deviation principles can be expressed explicitly in terms of relative entropies. We derive a large deviation principle for the degrees distribution of ErÖÖs-Réenyl graphs near criticality.Item Numeracy skills: the basis and beyond(Edicfam Ventures, 2010) Nortey, E.N.N.; Afrim, J.Item Possible adverse effect of high δ-alpha-tocopherol intake on hepatic iron overload: enhanced production of Vitamin C and the genotoxin, 8-hydroxy-2’-dexyguanosine(Toxicology Mechanisms and Methods 20(2): 96-104, 2010) Nortey, E.N.N.; Asare, A.G.; Ntobin, B.; Kew, M.C.; Kahler-Venter, P.Excess hepatic iron generates reactive oxygen species that result in oxidative stress and oxidative damage to the layer. Vitamins have hitherto been considered to be a possible remedy. The aim of this study was to determine if high doses of δ-a-tocopherol supplementation in iron overload would ameltorate the oxidative stress. Four groups of 20 males Wistar albino rats were studied: group 1 (control) was fed normal diet, group 2 (Fe) 0.75% Ferrocene iron, group 3 (FV gp) 0.75% Ferrocene/δ-a-tocopherol (10x RDA), group 4 (V gp) normal diet/δ-a-tocopherol. After 12 months, serum iron, reduced glutathione, catalase, Vitamin C., Oxygen Radical Absorbance Capacity, lipid peroxidation, 8-hydroxy-2’ dexyguanosine (8-OHdG), aspartate transaminase (AST), and alanine transaminase (ALT) were measured. Vitamin C levels were F gp=5.85 ± 0.13 (µmol/l) (p<0.05). 8-hydroxy 2’-dexyguanosine levels were F gp – 143.6 ± 6.4; FV gp – 179.2 ± 18.2 (ng/ml) (p,0.05). Oxidative liver damage, as determined by serum AST and ALT levels, was not attenuated by a-tocopherol. A positive correlation existed between vitamin C and 8-OHdg, suggesting possible a-tocopherol toxicity.Item Asymptotic Equipartition Properties for simple hierarchical and networked structures(Cambridge University Press, 2011) Doku-Amponsah, K.We prove asymptotic equipartition properties for simple hierarchical structures (modelled as multitype Galton-Watson trees) and networked structures (modelled as randomly coloured random graphs). For example, for large n, a networked data structure consisting of n units connected by an average number of links of order n / log n can be coded by about H × n bits, where H is an explicitly defined entropy. The main technique in our proofs are large deviation principles for suitably defined empirical measures.Item Reference intervals for common biochemical analytes in serum and plasma of a random adult population in the Greater Accra Region of Ghana(Clinical Laboratory, 2012-09) Asare, G.A.; Nortey, E.N.; Nkumpoi, T.; Amoah, A.G.B.Background: The reference interval (RI) is arguably the most widely used decision making tool in clinical practice. Using the manufacturer's reference values may not be appropriate for other ethnic populations. Objective: The objective was to determine the reference intervals (RI) of Ghanaians and compare them to that provided in kits. Methods: 6300 adults, 25-65 years were selected by cluster sampling from three communities in the Greater Accra Region, Ghana. A total of 4733 (male/female ratio = 1:1.5) participated. Fasting Blood Glucose (FF), 2-hour post-glucose plasma glucose (2HPP), total cholesterol (TCHOL), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), uric acid (UA), urea (U), albumin (ALB), alkaline phosphatase (ALP) were measured. Results: Male and female mean ages were 44.9 ±14.7 and 44.0 ±14.6 years, respectively. Most assays had mean values between the 25th and 75th percentile apart from HDL-C whose mean values fell within the 50th percentile. Thus half of the manufacturers RI (MRI) represented <25 percentile for FF, 2HPP, LDL-C, ALB and ALP. The MRI for Urea was <25th - >97.5th. Conclusions: Mean values of most of the parameters determined represented the 25th-75th and not the 95th or 97.5th percentile.Item Exponential approximation,method of types for empirical neighbourhood distributions for random graphs by random allocation(International journal of Statistics and Probability, 2014) Doku-Amponsah, KIn this article we find exponential good approximation of the empirical neigbourhood distribution ofsymbolled random graphs conditioned to a given empirical symbol distribution and empirical pair distribution.Using this approximation we shorten or simplify the proof of (Doku-Amponsah and Morters 2010, Theorem 2.5);the large deviation principle (LDP) for empirical neigbourhood distribution of symbolled random graphs. We alsoshow that the LDP for the empirical degree measure of the classical Erd˝os-R´enyi graph is a special case of (Doku-Amponsah and Moerters, 2010, Theorem 2.5). From the LDP for the empirical degree measure, we derive an LDP for the the proportion of isolated vertices in the classical Erd˝os-R´enyi graph.Item Large deviations, basic information theorem for fitness preferential attachment random networks(International journal of Statistics and Probability, 2014) Doku-Amponsah, K; Mettle, F.O; Ansah-Narh, TFor fitness preferential attachment random networks, we define the empirical degree and pair measure, which counts the number of vertices of a given degree and the number of edges with given fits, and the sample path empirical degree distribution. For the empirical degree and pair distribution for the fitness preferential attachment random networks, we find a large deviation upper bound. From this result we obtain a weak law of large numbers for the empirical degree and pair distribution, and the basic information theorem or an asymptotic equipartition property for fitness preferential attachment random networks.Item Effectiveness of community facilitator training in improving knowledge, attitudes, and confidence in relation to depression and suicidal behavior: Results of the OSPI-Europe intervention in four European countries.(Journal of Affective Disorders, 2014) Iddi, S; Van Audenhove, C; Coppens, E; Arensman, E; Coffey, C; Gusmao, R; Quintao, S; Costa, S; Hegerl, UCommunity facilitators (CFs), such as teachers, nurses and social workers, are well placed as gatekeepers for depression and suicidal behavior, but not properly prepared to provide preventive and supportive services. The current study aimed: (1) to improve CFs’ attitudes toward depression, knowledge on suicide, and confidence to detect suicidal behavior in four European countries and (2) to identify specific training needs across regions and CF groups.Item Empirical Bayes Estimates for Correlated Hierarchical Data with Overdispersion(Pharmaceutical Statistics, 2014) Iddi, S; Molenberghs, G; Aregay, M; Kalema, GAn extension of the generalized linear mixed model was constructed to simultaneously accommodate overdispersion and hierarchies present in longitudinal or clustered data. This so-called combined model includes conjugate random effects at observation level for overdispersion and normal random effects at subject level to handle correlation, respectively. A variety of data types can be handled in this way, using different members of the exponential family. Both maximum likelihood and Bayesian estimation for covariate effects and variance components were proposed. The focus of this paper is the development of an estimation procedure for the two sets of random effects. These are necessary when making predictions for future responses or their associated probabilities. Such (empirical) Bayes estimates will also be helpful in model diagnosis, both when checking the fit of the model as well as when investigating outlying observations. The proposed procedure is applied to three datasets of different outcome types.Item A methodology for stochastic analysis of share prices as Markov chains with finite states(SpringerPlus, 2014-11) Mettle, F.O.; Quaye, E.N.B.; Laryea, R.A.Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data. © 2014, Mettle et al.; licensee Springer.Item A marginalized combined gamma frailty and normal random-effects model for repeated, overdispersed, time-to-event outcomes(Communications in Statistics - Theory and Methods, 2014-11) Efendi, A.; Molenberghs, G.; Iddi, S.This article proposes a marginalized model for repeated or otherwise hierarchical, overdispersed time-to-event outcomes, adapting the so-called combined model for time-to-event outcomes of Molenberghs et al. (in press), who combined gamma and normal random effects. The two sets of random effects are used to accommodate simultaneously correlation between repeated measures and overdispersion. The proposed version allows for a direct marginal interpretation of all model parameters. The outcomes are allowed to be censored. Two estimation methods are proposed: full likelihood and pairwise likelihood. The proposed model is applied to data from a so-called comet assay and to data from recurrent asthma attacks in children. Both estimation methods perform very well. From simulation results, it follows that the marginalized combined model behaves similarly to the ordinary combined model in terms of point estimation and precision. It is also observed that the pairwise likelihood required more computation time on the one hand but is less sensitive to starting values and stabler in terms of bias with increasing sample size and censoring percentage than full likelihood, on the other, leaving room for both in practice. © 2014 Taylor & Francis Group, LLC.Item A methodology for stochastic analysis of share prices as Markov chains with finite states(2014-11-06) Mettle, F.O.; Quaye, E.N.B.; Laryea, R.A.Abstract Price volatilities make stock investments risky, leaving investors in critical position when uncertain decision is made. To improve investor evaluation confidence on exchange markets, while not using time series methodology, we specify equity price change as a stochastic process assumed to possess Markov dependency with respective state transition probabilities matrices following the identified state pace (i.e. decrease, stable or increase). We established that identified states communicate, and that the chains are aperiodic and ergodic thus possessing limiting distributions. We developed a methodology for determining expected mean return time for stock price increases and also establish criteria for improving investment decision based on highest transition probabilities, lowest mean return time and highest limiting distributions. We further developed an R algorithm for running the methodology introduced. The established methodology is applied to selected equities from Ghana Stock Exchange weekly trading data.Item Large deviation result for the empirical locality measure of typed random geometric graphs(International journal of Statistics and Probability, 2015) Doku-Amponsah, KIn this article for a finite typed random geometric graph we define the empirical locality distribution, which records the number of nodes of a given type linked to a given number of nodes of each type. We find large deviation principle (LDP) for the empirical locality measure given the empirical pair measure and the empirical type measure of the typed random geometric graphs. From this LDP, we derive large deviation principles for the degree measure and the proportion of detached nodes in the classical Erd˝os-R´enyi graph defined on [0, 1]d. This graphs have been suggested by (Canning and Penman, 2003) as a possible extension to the randomly typed random graphs.Item Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models(Springer Plus, 2015) Quaicoe, M.T.; Twenefour, F.B.K.; Baah, E.M.; Nortey, E.N.N.This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non station ary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box–Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.Item Large deviation principle for the empirical degree measure of preferential attachment random graphs.(International journal of Statistics and Probability, 2015) Doku-Amponsah, K; Mettle, F.O; Nortey, E.N.NWe consider preferential attachment random graphs which may be obtained as follows: It starts with a single node. If a new node appears, it is linked by an edge to one or more existing node(s) with a probability proportional to function of their degree. For a class of linear preferential attachment random graphs we find a large deviation principle (LDP) for the empirical degree measure. In the course of the prove this LDP we establish an LDP for the empirical degree and pair distribution see Theorem 2.3, of the fitness preferential attachment model of random graphs.Item Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models(2015-02) Nortey, E.N.N.; Ngoh, D.D.; Doku-Amponsah, K.; Ofori-Boateng, K.This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana. © 2015, Nortey et al.; licensee Springer.Item Modeling variations in the cedi/dollar exchange rate in Ghana: an autoregressive conditional heteroscedastic (ARCH) models(Springerplus, 2015-07) Quaicoe, M.T.; Twenefour, F.B.K.; Baah, E.M; Nortey, E.N.N.This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box–Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.Item A Markov chain Monte Carlo (MCMC) methodology with bootstrap percentile estimates for predicting presidential election results in Ghana.(Springerplus, 2015-09) Nortey, E.N.; Ansah-Narh, T.; Asah-Asante, R.; Minkah, R.Although, there exists numerous literature on the procedure for forecasting or predicting election results, in Ghana only opinion poll strategies have been used. To fill this gap, the paper develops Markov chain models for forecasting the 2016 presidential election results at the Regional, Zonal (i.e. Savannah, Coastal and Forest) and the National levels using past presidential election results of Ghana. The methodology develops a model for prediction of the 2016 presidential election results in Ghana using the Markov chains Monte Carlo (MCMC) methodology with bootstrap estimates. The results were that the ruling NDC may marginally win the 2016 Presidential Elections but would not obtain the more than 50 % votes to be declared an outright winner. This means that there is going to be a run-off election between the two giant political parties: the ruling NDC and the major opposition party, NPP. The prediction for the 2016 Presidential run-off election between the NDC and the NPP was rather in favour of the major opposition party, the NPP with a little over the 50 % votes obtained.Item Extreme value modelling of Ghana stock exchange index(Springerplus, 2015-11) Nortey, E.N.N.; Asare, K.; Mettle, F.O.Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000–2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q–Q, P–P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model.