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中文摘要：
进行空间自相关分析时,由于权重矩阵构建的主观性和选择单一时间截面数据随机性影响,存在可能的选择偏倚性问题。扫描统计量方法则有效地解决上述问题。研究选择甘肃省中南部51个区、县,采用Geoda0.9.5和Clusterseer0.2.3软件,对2001～2010年卫生部监测点上报的30 463例围产儿死亡病例进行空间自相关和扫描统计量分析,从不同尺度上对分析结果进行验证,证明时空扫描统计量方法有显著的比较优势。
英文摘要：
The problem of aggregation has been always one of the hot and focuses of the region research, and the positioning of aggregation is a prerequisite for continuing in-depth study in aggregation analysis. Aggrega- tion appears a high degree of sensitivity on the scale. When the aggregation was analyzed by using the spatial autocorrelation method, scale choices are often susceptible to subjective judgments of the researchers, and ex- ist the possibility of selection bias. So the spatial weight problem has been controversial. In addition, the aggre- gation is obviously space-dependent as well as time-dependent since different aggregation takes place within different time and space, which is neglected by the spatial autocorrelation method. Therefore, some scholars have been trying to explore better ways for aggregation analysis. In comparison, the spatial-temporal scan sta- tistic method raised by scholars as Kulldorff shows its superiority. This paper targets at 51 districts and coun- ties within the central and southern regions of Gansu Province, which are densely populated minority areas. Us-ing software Geoda0.9.5 and Clusterseer0.2.3, spatial autocorrelation analysis and space time scan statistical analysis were adopted about 30463 perinatal deaths during 2001 to 2010 according to the report delivered by monitoring points of Ministry of Health. It also gives a.detailed comparison between spatial autocorrelation and scanning statistic from the different perspectives of scale choices, scale transt~orming and space integra- tion, and, then tests the analysis results by appealing Sam 4.0. Through theoretical and empirical analysis, it fur- ther confirms that spatial-temporal scan statistic method has the significant advantage from the three aspects of scale selection, scale conversion, and spatial-temporal integration, which shows that it is not only effective measure to solve the problem of artificial selection, but also to achieve the-scale extrapolation and automatic conversion, and more favorable mix of three-dime
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