An ecological adjusted random effect model for property crime in Windhoek, Namibia (2011-2016) (Namibian Journal for Research, Science and Technology, 2022)
Count data that are zero inflated are often analysed using Zero-Inflated Negative Binomial GeneralizedLinear Mixed Model (ZINB-GLMM) when observations are correlated in ways that require randomeffects. This study investigated ecological factors influencing the number of property crimes inWindhoek by using data obtained from the Windhoek police over the period of six consecutive years(2011 to 2016). The ecological concepts were measured at different levels of aggregation. Limitedstudies in Windhoek have considered analysing crime data on Generalized Linear Mixed Model viaTemplate Model Builder (TMB) R-package. Crimes were counted with respect to Month, Season, Year,Location and Density. Property crime data contained more zeros than expected. When comparingmodels fitted, it was found that the Relative Risks (RR) were highly significant for models fitted viaNegative Binomial distribution. By adopting a ZINB-GLMM, the study attempted to address the potentialcovariates for Property crimes. The study showed that most of the variation property crimes was due tolocations. Crime was high during spring and winter time during the study period. The study furtherdiscovered that areas with high population densities had high crime intensity. Security patrols andsurveillance should be stepped up in Windhoek in high density suburbs especially during winter andspring seasons.
Keywords: Crime intensity; Random effects; Windhoek; Zeroinflated; ZINB-GLMM