Hernández Hernández Vladimir
Universidad Autónoma de Ciudad Juárez, CiudadJuárez, Chihuahua, México.
Rev Panam Salud Publica. 2012 May;31(5):396-402. doi: 10.1590/s1020-49892012000500007.
Prepare a tool for the exploratory study of road accidents in Ciudad Juarez, Chihuahua, Mexico, that exclusively applies the spatial geographical variable (location).
Observational and cross-sectional study that uses a Geographic Information System to explore the spatial nature of 13 305 road accidents recorded during 2008 and 2009 in Ciudad Juarez. Indicators were constructed that approximated the transit flow and included two variables: indices of the level of urbanization and population density.
The value of the global spatial autocorrelation was positive, indicating the presence of groupings that were identified through the spatial association indicators. There are road risk clusters located in areas with a high level of urbanization, low population density, and a high transit flow level.
The exploratory analysis of spatial data is a phase that precedes the use of multivariate techniques with a broader scope. The application of exploratory analysis techniques in itself makes it possible to standardize spatial groupings, identify global autocorrelation, and indicate the direction of the variables under study.
为墨西哥奇瓦瓦州华雷斯城道路交通事故的探索性研究准备一种工具，该工具专门应用空间地理变量（位置）。
采用观察性横断面研究，利用地理信息系统探索2008年和2009年在华雷斯城记录的13305起道路交通事故的空间性质。构建了近似交通流量的指标，包括两个变量：城市化水平指数和人口密度。
全局空间自相关值为正，表明通过空间关联指标识别出了聚类。道路风险聚类位于城市化水平高、人口密度低和交通流量水平高的地区。
空间数据的探索性分析是在更广泛范围内使用多变量技术之前的一个阶段。探索性分析技术的应用本身就能够对空间聚类进行标准化、识别全局自相关，并指明所研究变量的方向。
