%0 Journal Article %T Multiple Imputation for Missing Values in Homicide Incident Data: An Evaluation Using Unique Test Data %A Aki Roberts %A John M. Roberts %A Tim Wadsworth %J Homicide Studies %@ 1552-6720 %D 2018 %R 10.1177/1088767918778309 %X Incident-level homicide datasets such as the Supplementary Homicide Reports (SHR) commonly exhibit missing data. We evaluated multiple imputation methods (that produce multiple completed datasets, across which imputed values may vary) via unique data that included actual values, from police agency incident reports, of seemingly missing SHR data. This permitted evaluation under a real, not assumed or simulated, missing data mechanism. We compared analytic results based on multiply imputed and actual data; multiple imputation rather successfully recovered victim¨Coffender relationship distributions and regression coefficients that hold in the actual data. Results are encouraging for users of multiple imputation, though it is still important to minimize the extent of missing information in SHR and similar data %K Supplementary Homicide Reports (SHR) %K incident-level data %K missing data imputation %K quantitative methods %K victim¨Coffender relationship %U https://journals.sagepub.com/doi/full/10.1177/1088767918778309