Browsing by Author "Nabugoomu, Fabian"

Now showing 1 - 11 of 11
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    A Bayesian Approach to Regional and Local-Area Prediction From Crop Variety Trials
    (Journal of Agricultural, Biological, and Environmental Statistics, 2002) Theobald, Chris M.; Talbot, Mike; Nabugoomu, Fabian
    The inclusion of covariates in models for analyzing variety£ environmentaldata sets allows the estimation of variety yields for speci c locations within a region as well as for the region as a whole. Here we explore a Bayesian approach to the estimation of such effects and to the choice of variety using a possibly incomplete variety £ location£ year data set that includes location£ year covariates.This approachallows expert knowledge of the crop and uncertainty about local circumstances to be incorporated in the analysis. It is implemented usingMarkov chain Monte Carlo simulation.An example is used to illustrate the approach and investigate its robustness.
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    Burden of cumulative risk factors associated with non-communicable diseases among adults in Uganda: evidence from a national baseline survey
    (International Journal for Equity in Health, 2016) Wesonga, Ronald; Guwatudde, David; Bahendeka, Silver K.; Mutungi, Gerald; Nabugoomu, Fabian; Muwonge, James
    Modification of known risk factors has been the most tested strategy for dealing with noncommunicable diseases (NCDs). The cumulative number of NCD risk factors exhibited by an individual depicts a disease burden. However, understanding the risk factors associated with increased NCD burden has been constrained by scarcity of nationally representative data, especially in the developing countries and not well explored in the developed countries as well. Methods: Assessment of key risk factors for NCDs using population data drawn from 3987 participants in a nationally representative baseline survey in Uganda was made. Five key risk factors considered for the indicator variable included: high frequency of tobacco smoking, less than five servings of fruit and vegetables per day, low physical activity levels, high body mass index and raised blood pressure. We developed a composite indicator dependent variable with counts of number of risk factors associated with NCDs per participant. A statistical modeling framework was developed and a multinomial logistic regression model was fitted. The endogenous and exogenous predictors of NCD cumulative risk factors were assessed. Results: A novel model framework for cumulative number of NCD risk factors was developed. Most respondents, 38 · 6% exhibited one or two NCD risk factors each. Of the total sample, 56 · 4% had at least two risk factors whereas only 5.3% showed no risk factor at all. Body mass index, systolic blood pressure, diastolic blood pressure, consumption of fruit and vegetables, age, region, residence, type of residence and land tenure system were statistically significant predictors of number of NCD risk factors (p < 0 · 05). With exception to diastolic blood pressure, increase in age, body mass index, systolic blood pressure and reduction in daily fruit and vegetable servings were found to significantly increase the relative risks of exhibiting cumulative NCD risk factors. Compared to the urban residence status, the relative risk of living in a rural area significantly increased the risk of having 1 or 2 risk factors by a multiple of 1.55.
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    Determining Factors that Influence Household Food Insecurity in Uganda: A Case Study of Tororo and Busia Districts
    (International Journal of Sciences: Basic and Applied Research, 2014) Owino, Abraham Y.; Atuhaire, Leonard K.; Wesonga, Ronald; Nabugoomu, Fabian; Muwanga-Zaake, Elijah S.K.
    Addressing the national food insecurity problem requires an understanding and measurement of food insecurity at micro-level using a wide range of explanatory variables. Measurement of food insecurity is a challenge because it is a multi-faceted latent and continuous phenomenon explained by many variables. This paper examines these variables and applies exploratory factor analysis to identify variables which significantly influence household food insecurity and how they uniquely associate with specific food insecurity factors. Primary data on food availability, access, utilization and coping strategies were collected from 1175 randomly selected rural households in Tororo and Busia Districts of Uganda. Feasibility of exploratory factor analysis was analyzed using Pearson’s correlation coefficient.
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    Determining Food Insecurity: An Application of the Rasch Model with Household Survey Data in Uganda
    (International journal of food science, 2014) Owino, Abraham; Wesonga, Ronald; Nabugoomu, Fabian
    The inexplicable nature of food insecurity in parts of Uganda and worldwide necessitated an investigation into the nature, extent, and differentials of household food security.Themain objective of this study was to examine the food security dynamics and model household food insecurity.The Raschmodelling approach was employed on a dataset froma sample of 1175 (Tororo = 577; Busia = 598) randomly selected households in the year 2010. All households provided responses to the food security questions and none was omitted from the analysis. At 5 percent level of significance the analysis indicated that Tororo district average food security assessment (0.137 ± 0.181) was lower than that for Busia district (0.768 ± 0.177). All the mean square fit statistics were in the range of 0.5 to 1.5, and none of them showed any signs of distortion, degradation, or less productivity formeasurement.This confirmed that items used in this study were very productive for measurement of food security in the study area.The study recommends further analysis where item responses are ordered polytomous rather than the dichotomous item response functions used. Furthermore, consideration should be given to fit models that allow for different latent distributions for households with children and those without children and possibly other subgroups of respondents.
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    Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach
    (SpringerPlus, 2016) Wesonga, Ronald; Nabugoomu, Fabian
    The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiency
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    Investigation of the potential of fortified instant matooke flour in rehabilitation of malnourished children (Part 1): Optimal level of fortification of instant tooke flour porridge and its nutritional quality attributes
    (African Journal of Food Science, 2009) Isabirye Muranga, Florence; Kanyago, Miriam; Nabugoomu, Fabian; Ntambi, James M.
    The aim of this study was to optimize levels of incorporation of soybean and sesame flours into instant tooke (cooking banana) flour (ITF) porridge with respect to sensory quality. The flours were prepared using conventional dehydration procedures. A mixture design was developed for incorporating sesame and soybean flours into matooke flour. From the design thirteen porridge formulations were developed on which sensory evaluation was determined using 9-point hedonic scale. Sensory parameters determined were taste color, flavor, consistency, mouth feel and overall acceptability. Based on sensory evaluation, one optimal formulation was identified. Nutritional quality attributes of the optimum formulation were determined. Viscosity was determined using the Rapid Visco-Analyser. The optimal formulation was 64.90, 16.34 and 18.76 % matooke, soybean and sesame respectively. The results indicated that incorporation of soybean and sesame into ITF porridge significantly (p<0.001) enhanced its sensory quality attributes. Energy density and protein content of the optimum formulation was 502.12 Kcal and 11.1% respectively. Incorporation of sesame and soybean flours into ITF resulted in reduction in viscosity. The study suggested that fortification of ITF with soybean and sesame enhances sensory and nutritional quality.
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    Logit models for household food insecurity classification
    (American Journal of Theoretical and Applied Statistics, 2014) Owino, Abraham; Kiboijana Atuhaire, Leonard; Wesonga, Ronald; Nabugoomu, Fabian; Muwanga-Zaake, Elijah
    Micro-level measurement of food insecurity is a necessary approach towards a more feasible solution to the global problem for proper classification of households by food insecurity status. Measurement of food insecurity is a challenge because it is a multi-faceted latent and continuous phenomenon explained by a wide range of both quantitative and qualitative variables. In this paper, we examined the quantitative variables and applied exploratory factor analysis to identify which of them significantly influence household food insecurity. Logit models were then developed using the variables identified. Further, empirical data obtained from Tororo and Busia rural households in Uganda were used to fit the models. Four logit models based on four scenarios were developed and compared. The key findings pointed to the fact that if households were to be correctly analyzed and classified into the right food security category, a hybrid dependent variable that represents as many aspects of food insecurity as possible should be used. The model correctly classified 90 % of the combined households for two districts. However, when fitted for separate districts, it was established that 99% of households in Busia and 96% in Tororo district respectively, were found to be food insecure.
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    Modelling Airport Efficiency With Distributions Of The Inefficient Error Term: An Application Of Time Series Data For Aircraft Departure Delay
    (International Journal of Sciences: Basic and Applied Research, 2013) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, Peter; Mugisha, Xavier
    The study employs determinants of the aircraft departure delay to estimate airport efficiency. Two main parameters were applied to fit the stochastic frontier model using transcendental logarithmic function where both frontier and inefficiency models were generated. The estimated airport efficiencies over a period of 1827 days applying the half-normal and exponential distributions for the inefficiency error terms were (0.7498; δ=0.1417, n=1827) and (0.8181; δ=0.1224, n=1827) respectively. The correlation coefficient for the efficiency estimates (ρ=0.9791, n=1827, p<0.05) between the half-normal and exponential distributions showed no significant statistical difference. Further analysis showed that airport inefficiency was significantly associated with higher number of persons on board, lower visibility level, lower air pressure tendency, higher wind speed and a higher proportion of arrival aircraft delays. The study offers a contribution towards assessing the dynamics for the distribution of inefficient error term to estimate airport efficiency by employing both meteorological and aviation parameters. The study recommends that although either half-normal or exponential distributions could be used; the exponential distribution for the error term was found more suitable when estimating the efficiency score for the airport.
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    Optimisation of raw tooke flour, vital gluten and water absorption in tooke/wheat composite bread: Effect of raw tooke flour and vital gluten on wheat flour physicochemical and dough rheological properties (Part I)
    (African Journal of Food Science, 2010) Muranga, Florence I.; Mutambuka, Martin; Nabugoomu, Fabian; Lindhauer, M. G.
    Raw Tooke Flour (RTF) is a generic, shelf stable flour from matooke (a cooking banana variety) targeting the baking industry. However, its lack of gluten has hampered development of RTF/wheat composite bread. It is thus necessary to optimize levels of substitution of RTF into wheat flour with vital gluten as a processing aid for improving rheological and baking properties. The specific objective of this study was to determine effect of RTF (0 - 33%) and vital gluten (0 - 3%) on wheat flour pasting and dough rheological properties. The Rapid Visco Analyser was used to measure flour pasting properties while the Farinograph and Extensograph measured dough rheology. Response Surface Methodology (RSM) procedures were used to relate variables to dough rheological properties. RTF significantly increased the pasting profile of wheat flour (by increasing peak, minimum and final viscosities). It weakened the dough (by increasing degree of softening; reducing dough stability and extensibility) while vital gluten strengthened it. Water absorption increased with both variables while dough development time (DDT) was reduced by RTF. Though vital gluten improved dough properties, it did not effectively counteract the negative effects of RTF at the levels applied in the study.
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    Parameterized framework for the analysis of probabilities of aircraft delay at an airport
    (Journal of Air Transport Management, 2012) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, Peter
    The study analyses ground delays and air holding at Entebbe International Airport over five years. Daily probabilities for aircraft departure and arrival delays at are generated for each. The mean probabilities of delay for ground delays and air holding at 50% delay threshold levels are 0.94 and 0.82 that fall to 0.49 and 0.36 when 60% delay threshold levels are used. Simulations are performance for delay threshold levels to monitor for the trends of the daily probabilities for the study period. The general conclusion is that a parameter-based framework is best suited to determine the probability of aircraft delay at an airport.
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    Simulation of time series wind speed at an international airport
    (Simulation, 2019) Wesonga, Ronald; Nabugoomu, Fabian; Ababneh, Faisal; Owino, Abraham
    The sporadic and unstable nature of wind speed renders it very difficult to predict accurately to serve various decisions, such as safety in the air traffic flow and reliable power generation system. In this study we assessed the autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models on the wind speed time series problem. Data on wind speed and minimum and maximum temperatures were evaluated. Wind speed was established to follow a time series that fluctuated around ARIMA (0,1,1) and ARIMA (1,1,1). The optimal ANN model was established at 10 hidden neurons. The performance indices considered all indicated that the ANN wind speed model was superior to the ARIMA model. Wind speed prediction accuracy can be improved to secure the safety of air traffic flow as well support the implementation of a reliable and secure power generation system at the airport