Collaborative Research on the Importance of Spatial Effects in Applied Regression Analysis in Regional Science and Geography

回归分析是一种广泛使用的技术，用于测量两个变量之间或多个变量之间的关系。 该合作提案将使空间计量经济学家（Anselin）和空间统计学家（Griffith）能够解决使用回归分析来分析空间分布现象时出现的几个方法论问题。 当该技术应用于空间数据时，验证回归分析所需的一些假设并未得到满足。 例如，相邻的空间观测通常不是彼此独立的。 这种违反验证假设的行为如何影响空间回归的结果在很大程度上尚不清楚。 申请人将设计措施和测试，使希望对空间数据进行回归分析的学者能够确定空间现象如何影响回归分析及其结果，并且他们将制定可用于测试和验证涉及空间数据时从回归获得的结果的程序。 安塞林和格里菲斯将通过分发包含他们开发的方法的软件以及举办研讨会向感兴趣的科学家解释他们的结果来传播他们的研究结果。

Regression analysis is a widely-used technique for measuring relationships between two variables or among a number of variables. This collaborative proposal will enable a spatial econometrician (Anselin) and a spatial statistician (Griffith) to address several methodological issues that arise when regression analysis is used to analyze spatially-distributed phenomena. Some of the assumptions needed to validate regression analysis are not met when the technique is applied to spatial data. For example, adjacent spatial observations are commonly not independent of each other. How such violations of validating assumptions affect the results of spatial regression are largely unknown. The applicants will devise measures and tests that will enable scholars who wish to use regression analysis for spatial data to determine how spatial phenomena affect regression analysis and its results, and they will formulate procedures that can be used to test and validate the results obtained from regression when spatial data are involved. Anselin and Griffith will disseminate the results of their research by distributing software incorporating the methods they develop and by conducting workshops to explain their results to interested scientists.