New Approach to Evaluating Supplementary Homicide Report (SHR) Data Imputation, 1990-1995 - Wadsworth, Tim ([Verlag nicht ermittelbar], 2007)
The purpose of the project was to learn more about patterns of homicide in the United States by strengthening the ability to make imputations for Supplementary Homicide Report (SHR) data with missing values. Supplementary Homicide Reports (SHR) and local police data from Chicago, Illinois, St. Louis, Missouri, Philadelphia, Pennsylvania, and Phoenix, Arizona, for 1990 to 1995 were merged to create a master file by linking on overlapping information on victim and incident characteristics. Through this process, 96 percent of the cases in the SHR were matched with cases in the police files. The data contain variables for three types of cases: complete in SHR, missing offender and incident information in SHR but known in police report, and missing offender and incident information in both. The merged file allows estimation of similarities and differences between the cases with known offender characteristics in the SHR and those in the other two categories. The accuracy of existing data imputation methods can be assessed by comparing imputed values in an "incomplete" dataset (the SHR), generated by the three imputation strategies discussed in the literature, with the actual values in a known "complete" dataset (combined SHR and police data). Variables from both the Supplemental Homicide Reports and the additional police report offense data include incident date, victim characteristics, offender characteristics, incident details, geographic information, as well as variables regarding the matching procedure.