Abstract
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.
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