Monitoring the quality of statistical processes has been of great importance, mostly in industrial applications. Control charts are widely used for this purpose, but often lack the possibility to monitor survival outcomes. Recently, inspecting survival outcomes has become of interest, especially in medical settings where outcomes often depend on risk factors of patients. For this reason many new survival control charts have been devised and existing ones have been extended to incorporate survival outcomes. The R package success allows users to construct risk-adjusted control charts for survival data. Functions to determine control chart parameters are included, which can be used even without expert knowledge on the subject of control charts. The package allows to create static as well as interactive charts, which are built using ggplot2 (Wickham 2016) and plotly (Sievert 2020).
翻译:监测统计流程的质量一直非常重要,主要在工业应用中。控制图表被广泛用于这一目的,但往往缺乏监测生存结果的可能性。最近,对生存结果的检查引起了人们的兴趣,特别是在往往取决于病人风险因素的医疗环境中。为此原因,设计了许多新的生存控制图表,并扩大了现有图表,以纳入生存结果。R软件包的成功允许用户为生存数据建立风险调整控制图表。包括了确定控制图表参数的职能,即使没有关于控制图表的专家知识,也可以使用这些功能。软件包可以创建静态和互动的图表,这些图表是用ggplot2(Wickham 2016年)和巧妙地(Sievert 2020年)制作的。