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：统计过程的质量监控在工业应用中具有重要意义，控制图被广泛用于此目的，但通常缺乏监测生存结果的能力。近年来，尤其是当患者风险因素影响结局的医疗场景中，生存结果的检测引起了广泛关注。为此，许多新型生存控制图被设计出来，现有方法也被扩展以纳入生存结果。R语言success包允许用户为生存数据构建风险调整控制图，并包含确定控制图参数的函数，即使没有该领域的专业知识也能使用。该包支持创建基于ggplot2 (Wickham 2016)和plotly (Sievert 2020)的静态及交互式图表。