Statistics, Informatics & Qualitative Methods (SIQM) Core

项目摘要/摘要 研究核心：统计学、信息学和定性方法的核心 统计、信息学和定性方法(SIQM)核心将促进和支持农村卫生保健 递送科学。遵循集成的混合方法研究框架，并与 社区参与和外展(CEO)核心，我们寻求优化严谨、背景和进步 整个农村卫生保健提供科学中心的研究。SIQM核心的首要目标是 把定量和定性结合起来，提高农村重大卫生保健课题研究的严谨性 数据分析进入一个双向系统，其中一个提供给另一个。重点关注的具体领域包括 支持获得和开发独特的数据集，创新统计建模，构建 准确的统计推断、信息学和分析的扩展以及数据的敏锐性和影响力 视觉化。 核心中心将通过开发一个强大的研究数据仓库来支持该中心的研究人员 响应他们的研究目标，并对他们作为研究人员的发展和最终毕业提供双重帮助 到独立的资金。核心将使用包含医疗保险索赔、疾病 登记、美国人口普查、电子健康记录、地理空间和其他来源和形式的数据。至 作为补充，将从社区利益攸关方那里通过调查、访谈、 社区参与工作室，以及其他形式的混合方法研究。数据存储库将会增长 有时间在广度和深度上支持社区需求和优先事项，并通过 扩大他们在进一步开展工作和准备自己的工作时可以访问的数据范围 独立提案。除了集成和管理数据外，SIQM核心还将通过以下方式支持项目 开发和完善尖端统计方法，包括分层、纵向和地理空间 建模.解释观测数据混淆的因果推论方法(差异法 设计、倾向评分方法)；以及社会网络分析。核心将创造一个跨越 识别、共享和应用创新统计、地理信息学、数据科学和 用定性的方法来协助每个研究项目负责人。一旦建立，SIQM核心将协调 数据和方法，共享新的方法解决方案，并推广这些方法以供将来使用。

PROJECT SUMMARY/ABSTRACT Research Core: The Statistics, Informatics, and Qualitative Methods Core The Statistics, Informatics, and Qualitative Methods (SIQM) Core will promote and support rural health care delivery science. Following an integrated mixed-methods research framework and partnering with the Community Engagement and Outreach (CEO) Core, we seek to optimize the rigor, context, and advancement of research across the Center for Rural Health Care Delivery Science. The SIQM Core’s overarching goal is to improve the rigor of the research on important rural health care topics by integrating quantitative and qualitative data analyses into a two-way system where one feeds into the other. The specific areas of focus include supporting the attainment and development of unique datasets, innovative statistical modeling, the construction of accurate statistical inferences, the expansion of informatics and analytics, and the acuity and impact of data visualization. The Core will support the Center’s researchers by developing a robust research data warehouse that responds to their research goals and dually aids in their development as researchers and ultimate graduation to independent funding. The Core will work with datasets that incorporate health insurance claims, disease registry, US Census, electronic health records, geospatial and other sources and forms of data. To complement this, de novo data will be obtained from community stakeholders using surveys, interviews, Community-Engagement Studios, and other forms of mixed-methods research. The data repository will grow with time in breadth and depth to support community needs and priorities and support researchers by expanding the scope of data, to which they will have access as they further their work and prepare their own independent proposals. In addition to integrating and managing data, the SIQM Core will support projects by developing and refining cutting-edge statistical methods, including hierarchical, longitudinal, and geospatial modeling; causal inference methods to account for confounding in observational data (difference-in-difference designs, propensity score methods); and social network analysis. The Core will create an environment across the Center for identifying, sharing, and applying innovative statistical, geoinformatics, data science, and qualitative methods to assist each Research Project Leader. Once established, the SIQM Core will coordinate data and methods, share novel methodological solutions, and generalize these methods for future use.