This study explores issues associated with the data commonly used in homicide clearance research. Data collected from 2009 to 2011 case files (n = 252) were reviewed during interviews with investigators (n = 29). The multifaceted data collection approach produced a more comprehensive dataset than was available based solely upon case file reviews, with alterations to the data occurring in as many as 69% of the cases. The process advanced the precision of the data recorded, reduced missingness, and heightened detail on key variables. Significant differences were noted in multivariate analyses of the datasets when modeling clearances. Findings suggest contextualizing case file data is valuable.

这项研究探讨了与凶杀清除研究中常用数据相关的问题。在与研究者的访谈中（n = 29），回顾了从2009年至2011年病例档案中收集的数据（n = 252 ）。与仅基于案例文件审阅相比，多面数据收集方法产生的数据集更为全面，多达69％的案例发生了数据更改。该过程提高了记录数据的精度，减少了丢失，并提高了关键变量的细节。在对间隙建模时，在数据集的多元分析中注意到了显着差异。研究结果表明，案例文件数据的上下文化非常有价值。