• Login
    View Item 
    •   NWU-IR Home
    • Research Output
    • Faculty of Natural and Agricultural Sciences
    • View Item
    •   NWU-IR Home
    • Research Output
    • Faculty of Natural and Agricultural Sciences
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A regression model for predicting the likelihood of reporting a crime based on the victim’s demographic variables and their perceptions towards the police

    Thumbnail
    View/Open
    A Regression_Model_for_Predicting.pdf (760.6Kb)
    Date
    2020
    Author
    Montshiwa, Tlhalitshi Volition
    Pulenyane, Malebogo
    Metadata
    Show full item record
    Abstract
    Despite the growing criminal activities in South Africa,many victims still do not report the crimes, therefore there was a need to understand the determinants of the likelihood of reporting a crime in the country. Binary logistic regression is a supervisedmachine learning algorithmthat can assist in predicting the likelihood of reporting a crime but the selection of relevant variables to add in the model varies from one author to the other. Selection of theoretically sound and statistically relevant independent variables is key to achieving parsimonious multivariate models. This study sought to test the efficiency of some commonly used variable selection methods for logistic regression models in order to identify the most relevant determinants of the likelihood of reporting a crime of housebreaking. The study used 17 candidate variables such as the victims’ demographic variables and their perceptions on the police. The multivariate model fitted using stepwise selection was found to be a best fit for the data based on the lowest AIC, the highest classification accuracy rate and the highest Area under the Receiver Operating Characteristic curve. Themodel fitted using theHosmer-Lemeshow(H-L) algorithmwas the worst fit for the data. The study revealed a limitation of the stepwise selection method which is that this method may select different independent variables for each unique set of randomly selected observations of the same dataset. The study established a multivariate logistic regression model to predict the likelihood of a victim reporting a crime of housebreaking and the determinants thereof.
    URI
    http://hdl.handle.net/10394/39234
    https://doi.org/10.1515/spp-2020-0003
    Collections
    • Faculty of Natural and Agricultural Sciences [4788]

    Copyright © North-West University
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of NWU-IR Communities & CollectionsBy Issue DateAuthorsTitlesSubjectsAdvisor/SupervisorThesis TypeThis CollectionBy Issue DateAuthorsTitlesSubjectsAdvisor/SupervisorThesis Type

    My Account

    LoginRegister

    Copyright © North-West University
    Contact Us | Send Feedback
    Theme by 
    Atmire NV