Department of Statistics
Permanent URI for this collectionhttp://197.255.125.131:4000/handle/123456789/23133
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Item Comparison of confidence interval estimators: An index approach(Journal of Applied Probability and Statistics, 2019-04) Minkah, Richard; De wet, TertiusIn many statistical problems, several estimators are usually available for interval estimation of a parameter of interest, and hence, the selection of an appropriate estimator is important. The criterion for a good estimator is to have a high coverage probability close to the nominal level and a shorter interval length. However, these two concepts are in opposition to each other: high and low coverages are associated with longer and shorter interval lengths respectively. Some methods, such as bootstrap calibration, modify the nominal level to improve the coverage and thereby allow the selection of intervals based on interval lengths only. Nonetheless, these methods are computationally expensive. In this paper, we propose an index which offers an easy to compute approach of comparing confidence interval estimators based on a compromise between the coverage probability and the confidence interval length. We illustrate that the confidence interval index has range of values within the neighbourhood of the range of the coverage probability, [0,1]. In addition, a good confidence interval estimator has an index value approaching 1; and a bad confidence interval has an index value approaching 0. A simulation study was conducted to assess the finite sample performance of the index. The proposed index is illustrated with a practical example from the literatureItem Canonical Correlation Analysis Of Neonatal Anthropometric Indicators And Maternal Socio-Demographic Factors(INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, 2019-07) Affi, P.O.; Lartey, L.N.; Angkyiire, D.; Oppong, I.Abstract : The main objective of this study was to examine the relationship between neonatal anthropometric indicators (Baby head circumference, Baby full length and Baby weight) and maternal socio demographic factors (Gravidity, Parity, Educational level, Age, occupation of mother and number of ANC visit) using canonical correlation analysis. The neonatal anthropometric indicators were considered as depended (Y) variables whiles maternal socio demographic factors were considered as independent variables (X). The outcome of the canonical correlation analysis showed th at, there exists a significant relationship between neonatal anthropometric indicators (Baby head circumference, Baby full length and Baby weigh t) and maternal socio demographic factors (Gravidity, Parity, Educational level, Age, occupation of mother and number of ANC visi t). The total shared variance between the two set of variables was 69. 8 %. The study also showed that Baby head circumference has a positive relationship with maternal Age and also negative relationship with the remaining of the maternal socio demographic f actors whiles Baby full length and Baby weight also has a positive relationship with all the maternal socio demographic factors used in the study except maternal Age.Item Assessment of the determinants that influence the adoption of sustainable soil and water conservation practices in Techiman Municipality of Ghana(International Soil and Water Conservation Research, 2019) Darkwah, K.A.; Kwawu, J.D.; Agyire-Tettey, F.; Sarpong, D.B.This paper assesses the relationship between farmer characteristics and the degree to which nine soil and water conservation practices (SWCPs) are adopted by 300 maize farmers in Techiman Municipality, Ghana. Farmers were surveyed for their adoption of nine SWCPs, and 24 other characteristics including demographics, socio-economic factors, risk factors and costs of production. Sustainable soil and water conservation practices (SWCPs) in sub-Saharan Africa such as Ghana are important because they have positive effects on yield, increase sustainability of farming, stop degradation and reduce soil erosion. The adoption of sustainable soil and water conservation practices in the agricultural industry of Ghana has been variable. This study aims to explain differences in farmer adoption of SWCPs, by assessing factors that vary with the number of different SWCPs used by farmers. Hence, the Poisson model was used. The results show that farmer's household size, farm size, access to credit services and formal training of maize farmer have a positive significant association with the number of soil and water conservation practices adopted by maize farmers while distance to nearest output market, distance to input center, access to extension services, and risk of pest and diseases have a negative significant association with the number of soil and water conservation practices adopted by maize farmers at 5% significance level. The study concludes that any further research in Techiman Municipality on soil and water conservation practices should acknowledge the mixture of personal and demographic, institutional, socio-economic and risk factors. This suggests that agricultural policies formulated by the government should be aimed at supporting maize farmers to have access to extension service contact for frequent disseminating of agricultural technology information which is likely to increase the rate of adoption of soil and water conservation practices. © 2019 International Research and Training Center on Erosion and Sedimentation and China Water and Power PressItem Survival Pattern of First Accident among Commercial Drivers in the Greater Accra Region of Ghana(Accident Analysis and Prevention, 2017-06) Nanga, S.; Odai, N.A.; Lotsi, A.In this study, the average accident risk of commercial drivers in the Greater Accra region of Ghana and its associated risks were examined based on a survey data collected using paper-based questionnaires from 204 commercial drivers from the Greater Accra Region of Ghana. The Cox Proportional Hazards Model was used for multivariate analysis while the Kaplan-Meier (KM) Model was used to study the survival patterns of the commercial drivers. The study revealed that the median survival time for an accident to happen is 2.50 years. Good roads provided a better chance of survival than bad roads and experienced drivers have a better chance of survival than the inexperienced drivers. Age of driver, alcohol usage of driver, marital status, condition of road and duration of driver's license were found to be related to the risk of accident.Item Effect of Covariate Misspecifications in the Marginalized Zero-Inflated Poisson Model(Monte Carlo Methods and Applications, 2017-01) Iddi, S.; Nwoko, E.O.Count outcomes are often modelled using the Poisson regression. However, this model imposes a strict mean-variance relationship that is unappealing in many contexts. Several studies in the life sciences result in count outcomes with excessive amounts of zeros. The presence of the excess zeros introduces extra dispersion in the data which cannot be accounted for by the traditional Poisson regression. The zero-inflated Poisson (ZIP) and zero-inflated negative binomial models are popular alternative. The zero-inflated models comprise two key components; a logistic part which models the zeros, and a Poisson component to handle the positive counts. Both components allow the inclusion of covariates. Civettini and Hines [3] investigated misspecification effects in the zero-inflated negative binomial regression models. Long,Preisser, Herring and Golin [10] proposed a so-called marginalized zero-inflated Poisson (MZIP) model that allows direct marginal interpretation for fixed effect estimates to overcome the often sub-population specific interpretation of the traditional zero-inflated models. In this research, the effects of misspecification of components of the MZIP regression model are investigated through a comprehensive simulation study. Two different incorrect specifications of the components of an MZIP model were considered, namely ‘Omission’ and ‘Misspecification’. Bias, standard error (precision) of estimates and mean square error (MSE) are computed while varying the sample size. Type I error rates are also evaluated for the misspecified models. Results of a Monte Carlo simulation are reported. It was observed that omissions in both parts of the models lead to biases in the estimated parameters. The intercept parameters were the most severely affected. Furthermore, in all the types of omissions, parameters in the zero-inflated part of the models were much affected compared to the Poisson part in terms of both bias and MSE. Generally, bias and MSE decrease as sample sizes increase for all parameters. It was also found that misspecification can either increase, preserve or decrease the type I error rates depending on the sample size.Item Recognition of Face Images under Angular Constraints Using DWT-PCA/SVD Algorithm(Far East Journal of Mathematical Sciences, 2017-12) Asiedu, L.; Mettle, F.O.; Nortey, E.N.N.; Yeboah, E.S.The intricacy of a face’s features originates from continuous changes in the facial features that take place over time. Regardless of these changes, we are able to recognize a person very easily. In human interactions, the articulation and perception of constraints; like head-poses, facial expressions form a communication channel that is additional to voice and that carries crucial information about mental, emotional and even physical states of a conversation. Automatic face recognition is worthwhile, since an efficient and resilient recognition system is useful in many application areas. This paper presents an evaluation of the performance of principal component analysis with singular value decomposition using discrete wavelet transform (DWT-PCA/SVD) for preprocessing under angular constraints. Ten individuals from Massachusetts Institute of Technology (MIT) database (2003-2005) captured under the specified angular constraints were considered for recognition runs. Friedman’s rank sum test was used to ascertain whether significant differences exist between the median recognition distances of the various constraints from their straight-pose. Recognition rate and runtime were adopted as the numerical evaluation methods to assess the performance of the study algorithm. All numerical and statistical computations were done using Matlab. The results of the Friedman’s rank sum test show that the higher the degrees of head-pose, the larger the recognition distances and that at and above, the recognition distances become profoundly larger compared to the head-pose. The numerical evaluations show that DWT-PCA/SVD face recognition algorithm has an appreciable average recognition rate (87.5%) when used to recognize face images under angular constraints. Also, the recognition rate decreases for head-poses greater than Discrete wavelet transform is recommended as a viable noise removal mechanism that should be adopted during image preprocessing.Item Asymptotics of the Partition Function of Ising Model on Inhomogeneous Random Graphs(Far East Journal of Mathematical Sciences, 2017-12) Doku-Amponsah, K.For a finite random graph, we defined a simple model of statistical mechanics. We obtain an annealed asymptotic result for the random partition function for this model on finite random graphs as $n,$ the size of the graph is very large. To obtain this result, we define the \emph{ empirical bond distribution}, which enumerates the number of bonds between a given couple of spins, and \emph{ empirical spin distribution}, which enumerates the number of sites having a given spin on the spinned random graphs. For these empirical distributions we extend the large deviation principle(LDP) to cover random graphs with continuous colour laws. Applying Varandhan Lemma and this LDP to the Hamiltonian of the Ising model defined on Erdos-Renyi graphs, expressed as a function of the empirical distributions, we obtain our annealed asymptotic result.Item Causes of death at the University of Ghana Hospital in Accra-a 37-year review (1979-2015)(International Health, 2018-04) Sutherland, E.K.; Ansa, G.A.; Baiden, F.; Quaye, E.N.B.; Amoabeng, A.A.; Amenuveve, C.Background: An analysis of the causes of death in developing countries is needed to improve healthcare delivery. The aim of this study was to conduct a descriptive analysis of the causes of death at the University of Ghana Hospital from 1979 to 2015. Methods: Data were extracted from the electronic database of the University of Ghana Hospital. Diseases were grouped into three broad groups of causes of death as per the Global Burden of Disease cause list, with some diseases of epidemiological importance outlined and analysed by age, gender and time in years. Results: Of 3263 deaths, almost 60% were caused by non-communicable diseases (NCDs) that consisted of cancers, diabetes mellitus, cardiovascular diseases and other systemic conditions. Deaths by malaria, tuberculosis, diarrhoeal diseases and immunizable childhood diseases declined over the years while deaths from NCDs increased. The majority of cases of NCDs were due to cardiovascular disorders. Conclusions: The study suggests that Ghana has a double burden of disease with predominantly NCDs from cardiovascular diseases, metabolic disorders and cancers. Although malaria and other childhood-related illnesses have declined significantly, human immunodeficiency virus is fuelling the communicable disease mortalities. There is an urgent need to scale up NCD control interventions while strengthening communicable disease control.Item Estimating the Evolution of Disease in the Parkinson’s Progression Markers Initiative(Neurodegenerative Diseases, 2018-08) Iddi, S.; Li, D.; Aisen, P.S.; Rafii, M.S.; Litvan, I.; Thompson, W.K.; Donohue, M.C.Parkinson's disease is the second most common neurological disease and affects about 1% of persons over the age of 60 years. Due to the lack of approved surrogate markers, confirmation of the disease still requires postmortem examination. Identifying and validating biomarkers are essential steps toward improving clinical diagnosis and accelerating the search for therapeutic drugs to ameliorate disease symptoms. Until recently, statistical analysis of multicohort longitudinal studies of neurodegenerative diseases has usually been restricted to a single analysis per outcome with simple comparisons between diagnostic groups. However, an important methodological consideration is to allow the modeling framework to handle multiple outcomes simultaneously and consider the transitions between diagnostic groups. This enables researchers to monitor multiple trajectories, correctly account for the correlation among biomarkers, and assess how these associations may jointly change over the long-term course of disease. In this study, we apply a latent time joint mixed-effects model to study biomarker progression and disease dynamics in the Parkinson's Progression Markers Initiative (PPMI) and examine which markers might be most informative in the earliest phases of disease. The results reveal that, even though diagnostic category was not included in the model, it seems to accurately reflect the temporal ordering of the disease state consistent with diagnosis categorization at baseline. In addition, results indicated that the specific binding ratio on striatum and the total Unified Parkinson's Disease Rating Scale (UPDRS) show high discriminability between disease stages. An extended latent time joint mixed-effects model with heterogeneous latent time variance also showed improvement in model fit in a simulation study and when applied to real data.Item Effectiveness of Potential Interventions to Change Gendered Social Norms on Prevalence of Intimate Partner Violence in Uganda: a Causal Inference Approach(Prevention Science, 2019-03) Kadengye, D.T.; Iddi, S.; Hunter, L.; McCoy, S.I.Evidence of the effectiveness of programs to change gendered social norms related to intimate partner violence (IPV) is growing, but their potential to significantly impact actual occurrence of IPV at population level is lacking. We study whether modest changes in gendered social norms related to wife-beating can result in significant changes in the incidence of emotional, physical, and sexual IPV among ever married women in Uganda. We employ an imputation-based causal inference approach, based on nationally representative Demographic Health Survey data. The steps are (1) model the association between adjusted neighborhood norms and experiences of IPV using a random effects logistic regression model, (2) impute unobserved counterfactual probabilities of experiencing IPV for each woman while manipulating her neighborhood norms by setting it to different values, (3) average the probabilities across the population, and (4) bootstrap confidence intervals. Results show that statistically significant inverse associations between more prohibitive neighborhood IPV norms and women's experiences of different forms of IPV at the population level exist. The effect is however small, that even if an entire community disapproves of wife-beating, incidence of IPV falls by about 10 percentage points to 48.5% (95% CI 46.0%-50.9%) from the observed value of 57.6% (95% CI 55.2%-59.9%). Furthermore, changes in neighborhood social norms are found to have no statistical significant effect on the incidence of sexual violence. In conclusion, changing gendered social norms related to wife-beating will not result in significant reductions in different forms for IPV at the population level.
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