Browsing by Author "Belina, Merga"

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    Fully Nonparametric Methods for Partially Complete Data in Repeated Measures Design
    (Addis Ababa University, 2018-07-04) Belina, Merga; Wencheko, Eshetu (professor); Solomon W, Harrar (pHd)
    In this dissertation, two related but distinct problems are studied. The first one is a fully nonparametric rank-based method for comparing samples with partially paired data. Partially-paired (correlated) data naturally arise, for example, as a result of missing values, in incomplete block designs or meta analysis. In the nonparametric setup, treatment effects are characterized in terms of functionals of distribution functions and the only assumption needed is that the marginal distributions to be non-degenerate. The setup accommodates binary, ordered categorical, discrete and continuous data in a seamless fashion. The use of nonparametric effects also addresses the Behrens-Fisher problem from the nonparametric point of view and allows construction of confidence intervals. Although, the nonparametric methods are mainly asymptotic, methods for small sample approximations are also proposed. The second problem studied is also a fully nonparametric rank-based method but for partially repeated measures data. Here a vector of nonparametric relative effect measures are defined and linear hypotheses on these effects are considered. A multitude of tests are available for hypothesis related to a vector of relative effects. We focus on asymptotic results and finite sample performance for Wald-type statistic (WTS), ANOVA-type statistic (ATS) and Multiple Comparison Test Procedure (MCTP). Notwithstanding the limitation that the theory is thoroughly investigated for the three time point case, the results can formally be extended to the more general set up but the involved expressions will be much more complicated. The finite sample behavior of the tests are investigated via simulation studies. The results provide numerical evidence of favorable performance of the nonparametric method. The new methods vi have overwhelming power advantage when treatment effects are reflected in the shape of the distribution while they perform comparably better with parametric methods for location-type alternatives. Data from a therapeutic-drug clinical trial and a randomized controlled epidemiological study are used to illustrate the application of the methods.
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    Predictors of Burden on Caregivers of Patients of Schizophrenia and Bipolar Disorder: The Case of Butajira, Ethiopia Merga BeJilla
    (Addis Ababa University, 2008-07) Belina, Merga; Abegaz, Fentaw (PhD)
    The aim of the study was to investigate the prevalence and nature of the objective burden experienced by caregivers of schizophrenia and bipolar disorder patients. Also to compare the results from the two statistical methods, polytomous logi stic regression and discriminant analysis in correctly classifying and selecting important explanatory variables of burden on caregivers in psychiatric patients. A total of 514 patients were included in this study. Burden on the caregivers was assessed in telms of how much the caregiver's life was affected by the presence of the illness in the family. Results indicate that 36.5% of the caregivers experienced no burden, whereas 36.9% of them experienced moderate burden. The polytomous ordinal logistic regression classified 67.2% of the caregivers in their respective burden group, whereas the discriminant analysis classified 64.7% of the caregivers correctly. The polytomous ordinal logistic regression shows a slight improvement in correctly classifying caregivers over multiple discriminant analysis. Based on the findings of the present study we conclude that high burden on the caregivers is signi ficantly characterized by dependency status of the patient, emotional helps given to the care giver from the society, negative and positive symptom of the patient. The results call for more attention to be given to reduce patients ' positive and negative symptoms, to create awareness in the society to give emotional helps to the caregivers and to economically support the patients so as to minimize their dependency on their caregivers.