Many theories in political science predict the spatial clustering of similar behaviors among neighboring units of observation. This spatial autocorrelation poses implications for both inference and modeling that are distinct from the more familiar serial dependence in time series analysis. In this paper, I examine how political scientists can diagnose and model the spatial dependence that is pr...

This retrospective population-based study was conducted to analyze spatial patterns of tuberculosis (TB) incidence in Si Sa Ket province, Thailand. TB notification data from 2004 to 2008 collected from TB clinics throughout the province was used along with population data to reveal a descriptive epidemiology of TB incidences. Global clustering patterns of the occurrence were assessed by using g...

spatial environmental autocorrelation is a known phenomenon in the environmental studies explaining spatial relationship of environmental characteristics of different geographical units. different mechanisms have been proposed to clarify how the environments of especially neighboring countries response to changes of each other. this paper attempts to propose a new mechanism, namely spatial inst...

1. introduction the long-term result of cooperation between environmental factors and circulation patterns determines the arrangement of type and manner in temperature heat islands in geographical areas. the knowledge about space dispersion in geographical areas provides the grounds for sound programming and proper environmental decision making. the information about time and place distribution...

background: myocardial infarction (mi) is a leading cause of mortality and morbidity in iran. no spatial analysis of mi has been conducted to date. the present study was conducted to determine the pattern of mi incidence and to identify the associated factors in iran by province. materials and methods: th is study has two parts. one part is prospective and hospital-based, and the other part is ...

Global assessment of human-environment interactions is intrinsically hierarchical, requiring that we infer how local and regional processes will manifest themselves in regional and global conditions, respectively. But the ability to embed local intensive case studies of social and ecological processes within spatially extensive regional or global demographic and environmental data is hindered b...