Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, 20850, USA.
Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, Rockville, MD, 20850, USA.
Int J Health Geogr. 2021 Mar 18;20(1):13. doi: 10.1186/s12942-021-00267-z.
Cancer epidemiology studies require sufficient power to assess spatial relationships between exposures and cancer incidence accurately. However, methods for power calculations of spatial statistics are complicated and underdeveloped, and therefore underutilized by investigators. The spatial relative risk function, a cluster detection technique that detects spatial clusters of point-level data for two groups (e.g., cancer cases and controls, two exposure groups), is a commonly used spatial statistic but does not have a readily available power calculation for study design.
We developed sparrpowR as an open-source R package to estimate the statistical power of the spatial relative risk function. sparrpowR generates simulated data applying user-defined parameters (e.g., sample size, locations) to detect spatial clusters with high statistical power. We present applications of sparrpowR that perform a power calculation for a study designed to detect a spatial cluster of incident cancer in relation to a point source of numerous environmental emissions. The conducted power calculations demonstrate the functionality and utility of sparrpowR to calculate the local power for spatial cluster detection.
sparrpowR improves the current capacity of investigators to calculate the statistical power of spatial clusters, which assists in designing more efficient studies. This newly developed R package addresses a critically underdeveloped gap in cancer epidemiology by estimating statistical power for a common spatial cluster detection technique.
癌症流行病学研究需要足够的能力来准确评估暴露与癌症发病率之间的空间关系。然而，空间统计的能力计算方法较为复杂且尚未得到充分发展，因此研究人员对此利用不足。空间相对风险函数是一种常用的空间统计学方法，用于检测两组（例如癌症病例和对照组、两种暴露组）的点级数据的空间聚类，但它没有现成的研究设计的能力计算。
我们开发了 sparrpowR 作为一个开源的 R 包，用于估计空间相对风险函数的统计能力。sparrpowR 根据用户定义的参数（例如样本量、位置）生成模拟数据，以高统计能力检测空间聚类。我们展示了 sparrpowR 的应用，该应用对一项旨在检测与众多环境排放点源相关的癌症发病空间聚类的研究进行了能力计算。进行的能力计算演示了 sparrpowR 计算空间聚类检测局部能力的功能和实用性。
sparrpowR 提高了研究人员计算空间聚类统计能力的能力，从而有助于设计更有效的研究。这个新开发的 R 包通过估计一种常见的空间聚类检测技术的统计能力，解决了癌症流行病学中一个严重缺乏发展的差距。
