TY  - JOUR
PY  - 2018//
TI  - Multiple imputation for missing values in homicide incident data: an evaluation using unique test data
JO  - Homicide studies
A1  - Roberts, John M.
A1  - Roberts, Aki
A1  - Wadsworth, Tim
SP  - 391
EP  - 409
VL  - 22
IS  - 4
N2  - 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-offender relationship distributions and regression coefficients that hold in the actual data. <br><br>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.<p />  <p>Language: en</p>
LA  - en
SN  - 1088-7679
UR  - http://dx.doi.org/10.1177/1088767918778309
ID  - ref1
ER  -