2 resultados para Statistical models

em CORA - Cork Open Research Archive - University College Cork - Ireland


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In rural Ethiopia, among other things, lack of adequate financial service is considered as the basic problem to alleviate rural poverty and to solve the problem of food insecurity. Commercial banks are restricted to urban centres. Providing rural financial service through RUSACCO to the poor has been proposed as a tool for economic development and for achieving food security. Evidence from research in this regard has been so far scanty, especially in rural Ethiopia. The aims of this study are to analyze the determinants of membership, to identify socioeconomic and demographic factors that influence members’ participation in RUSACCOs and to quantify the impact of RUSACCOs on member households’ food security. The study was conducted in two purposely selected woredas in the Amhara region one from food insecure (Lay Gayint woreda) and the other from food secure (Dejen woreda). Six RUSACCOs were selected randomly from these two woredas. Both qualitative and quantitative data were collected. Key informant interviews, focus group discussions and survey techniques were used to collect primary data. Collected data was then analyzed using mixed methods depending on the nature of data. For quantitative data analysis appropriate statistical models were used. The study result reveals that the number of members in each RUSACCO is very small. However, the majority of non-member respondents are willing to join RUSACCO. Lack of information about the benefits of RUSACCO membership is the main problem why many rural poor do not join RUSACCOs. Members participate in different aspects of the cooperatives, starting from attending general assembly up to board membership. They also participate actively in saving and borrowing activities of RUSACCO. The majority of the respondents believe the RUSACCO is a vital instrument in combating food insecurity. The empirical findings indicate that gender, marital status, occupation, educational level, participation in local leadership and participation in other income generation means determine the decision of rural poor to join a RUSACCO or not. The amount of saving is determined by household head occupation, farming experience and income level. While age of household head, primary occupation, farming experience, date of membership, annual total consumption expenditure, amount of saving and participation in other income generation activities influence members’ amount of borrowing by RUSACCO members. Finally, the study confirms that RUSACCO participation improves household food security. RUSACCO membership has made positive impact on household total consumption expenditure and food expenditure.

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Dynamic positron emission tomography (PET) imaging can be used to track the distribution of injected radio-labelled molecules over time in vivo. This is a powerful technique, which provides researchers and clinicians the opportunity to study the status of healthy and pathological tissue by examining how it processes substances of interest. Widely used tracers include 18F-uorodeoxyglucose, an analog of glucose, which is used as the radiotracer in over ninety percent of PET scans. This radiotracer provides a way of quantifying the distribution of glucose utilisation in vivo. The interpretation of PET time-course data is complicated because the measured signal is a combination of vascular delivery and tissue retention effects. If the arterial time-course is known, the tissue time-course can typically be expressed in terms of a linear convolution between the arterial time-course and the tissue residue function. As the residue represents the amount of tracer remaining in the tissue, this can be thought of as a survival function; these functions been examined in great detail by the statistics community. Kinetic analysis of PET data is concerned with estimation of the residue and associated functionals such as ow, ux and volume of distribution. This thesis presents a Markov chain formulation of blood tissue exchange and explores how this relates to established compartmental forms. A nonparametric approach to the estimation of the residue is examined and the improvement in this model relative to compartmental model is evaluated using simulations and cross-validation techniques. The reference distribution of the test statistics, generated in comparing the models, is also studied. We explore these models further with simulated studies and an FDG-PET dataset from subjects with gliomas, which has previously been analysed with compartmental modelling. We also consider the performance of a recently proposed mixture modelling technique in this study.