Luke Douglas A
Saint Louis University School of Public Health, Saint Louis, MO 63104, USA
Am J Community Psychol. 2005 Jun;35(3-4):185-200. doi: 10.1007/s10464-005-3397-z.
Community science has a rich tradition of using theories and research designs that are consistent with its core value of contextualism. However, a survey of empirical articles published in the American Journal of Community Psychology shows that community scientists utilize a narrow range of statistical tools that are not well suited to assess contextual data. Multilevel modeling, geographic information systems (GIS), social network analysis, and cluster analysis are recommended as useful tools to address contextual questions in community science. An argument for increased methodological consilience is presented, where community scientists are encouraged to adopt statistical methodology that is capable of modeling a greater proportion of the data than is typical with traditional methods.
社区科学有着运用与情境主义核心价值相一致的理论和研究设计的丰富传统。然而，一项对发表在美国《社区心理学杂志》上的实证文章的调查显示，社区科学家使用的统计工具范围狭窄，并不适合评估情境数据。多层建模、地理信息系统（GIS）、社会网络分析和聚类分析被推荐为解决社区科学中情境问题的有用工具。本文提出了一个提高方法一致性的论点，鼓励社区科学家采用能够比传统方法更典型地对更大比例的数据进行建模的统计方法。
