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Using Network and Spatial Data to Better Target Overdose Prevention Strategies in Rural Appalachia

机译:利用网络和空间数据更好地针对农村阿巴拉契亚地区的过量用药预防策略

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摘要

Example network data for this analysis. Eight directed ties. Of these, 4 are reciprocal ties (c, d, g, and h) and 4 are unreciprocated, or one-directional ties (a, b, e, and f). For the analyses presented in this paper, we assumed that a relationship between two individuals existed if at least one person in the pair indicated knowing the other person in the pair. For example, in , individual 1 reported knowing individual 2, but individual 2 did not report knowing individual 1. The symmetrized or undirected version of ( ). For the dyadic analyses, which focused on relationships, we assumed (as shown in b) that if at least one individual reported a relationship to another, that the tie was reciprocated. Thus, shows two arrows between these individuals (a and a ). The dyadic analysis in this example would therefore consists of 12 ties and an individual-level analysis would include 6 individuals. As displayed in , this means that there are two one-degree paths (i.e., one in either direction) between all connected nodes in the network. Dyadic analyses require that there be information on the relationship between the two individuals. In cases like the relationship between individual 2 and individual 4, each individual provided information about the relationship with the other and this information may not agree. For example, the relationship information reported by individual 2 (represented by tie d) and by individual 4 (represented by tie c) may be different. We therefore used information reported about the relationship between 4 and 2 by individual 4 (represented by tie c) for analyses interested in the directed path between 4 and 2; and information about the relationship reported by 2 (represented by tie d) for the directed path between 2 and 4. In scenarios where only one individual in the pair reported knowing the other (i.e., the tie represented by between individuals 1 and 2), we used the information about the relationship reported by individual 1 for the path represented by both a and a in ( ). For the egocentric analyses, we assumed that individuals 1 and 3 had only one first-degree network member, individuals 5 and 6 had two first-degree network members, and individuals 2 and 4 had 3 first-degree network members
机译:用于此分析的示例网络数据。八个定向联系。其中,4个是倒扣(c,d,g和h),4个是倒扣或单向领带(a,b,e和f)。对于本文中提出的分析,我们假设如果一对中的至少一个人表示知道该对中的另一个人,则两个人之间存在关系。例如,在中,个人1报告知道个人2,但是个人2未报告知道个人1。()的对称或无向版本。对于侧重于关系的二元分析,我们假设(如图b所示),如果至少一个人报告与另一个人有关系,则领带是往复的。因此,显示了这些个体之间的两个箭头(a和a)。因此,此示例中的二元分析将由12个联系组成,而单个级别的分析将包括6个个体。如中所示,这意味着网络中所有连接的节点之间有两条单度路径(即,任一方向一条)。二进位分析要求提供有关两个人之间关系的信息。在诸如个人2和个人4之间的关系之类的情况下,每个人都提供了有关彼此关系的信息,而该信息可能会不一致。例如,由个人2(由领带d表示)和由个人4(由领带c表示)报告的关系信息可以不同。因此,我们使用报告的有关个体4与2之间的关系的信息(用领带c表示)来分析对4与2之间的有向路径感兴趣的分析。以及有关2到4之间的有向路径的2所报告的关系的信息(用领带d表示)。在一对中只有一个人知道另一个的情况下(即,个人1和2所代表的领带),我们在()中使用有关个人1报告的关系的信息来表示由a和a表示的路径。对于自我中心分析,我们假设个人1和3仅具有一个一级网络成员,个人5和6具有两个一级网络成员,而个人2和4具有3个一级网络成员。

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