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The nearest neighbour analysis method has been developed to determine whether a disease case may be regarded as being unusually close to other neighbouring cases of the same disease. Using this method, each disease case is classified as spatially 'clustered' or 'non-clustered'. The method is also used to provide a test for global clustering. 'Clusters' are constructed by amalgamating geographically neighbouring clustered cases into one contiguous 'cluster area'. This paper describes a method for studying differences between clustered and non-clustered cases, in terms of case 'attributes'. These attributes may be person related, such as age and sex, or area based, such as geographical isolation. The area-based variables are subject to geographical correlation. The comparison of clustered and non-clustered cases may reveal similarities or differences, which may, in turn, give clues to disease aetiology. A method for studying 'linkage' or similarities in attributes between cases that occur in the same clusters is also described. The methods are illustrated by application to incidence data for leukaemias and lymphomas.  相似文献   
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With rapid improvements in medical treatment and health care, many datasets dealing with time to relapse or death now reveal a substantial portion of patients who are cured (i.e., who never experience the event). Extended survival models called cure rate models account for the probability of a subject being cured and can be broadly classified into the classical mixture models of Berkson and Gage (BG type) or the stochastic tumor models pioneered by Yakovlev and extended to a hierarchical framework by Chen, Ibrahim, and Sinha (YCIS type). Recent developments in Bayesian hierarchical cure models have evoked significant interest regarding relationships and preferences between these two classes of models. Our present work proposes a unifying class of cure rate models that facilitates flexible hierarchical model-building while including both existing cure model classes as special cases. This unifying class enables robust modeling by accounting for uncertainty in underlying mechanisms leading to cure. Issues such as regressing on the cure fraction and propriety of the associated posterior distributions under different modeling assumptions are also discussed. Finally, we offer a simulation study and also illustrate with two datasets (on melanoma and breast cancer) that reveal our framework's ability to distinguish among underlying mechanisms that lead to relapse and cure.  相似文献   
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Social Indicators Research - This study investigates the causal relationship between health conditions and living arrangements of elderly people in contemporary China. The endogeneity between...  相似文献   
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ABSTRACT.Objectives: We conducted a survey to obtain information concerning how mothers of children with DSD represent the diagnosis. Methods: We examined our findings through IPA methodology. Results: We observed a crisis of meaning, based on the inability to classify their child with a milestone of the social experience: the gender category. That risks of slipping into adempitive adherences to medical knowledge or hasty decisions about the health of the child. Conclusions: It's necessary to structure spaces with medical-psychological teams, for allowing these families to manage the condition in relation to the choices, and the daily context, of their children.  相似文献   
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Contesting Communities has an interesting title and, as such,provided an enticement into the book but what started out asa journey of hope and excitement unfortunately ended in disappointment.While there are some very interesting parts to this book, ultimatelyit failed on a number of different fronts. It appears to bea book about community and therefore of interest to the readershipof the journal. The subtitle, The Transformation of WorkplaceCharity, hints at its real subject matter, that is fundraisingby non-profit organizations  相似文献   
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