Using a weighted bootstrap approach to identify risk factors associated with the sexual activity of entering first-year students at UWC
| dc.contributor.advisor | Blignaut, Renette | |
| dc.contributor.author | Brydon, Humphrey | |
| dc.date.accessioned | 2014-06-05T12:43:40Z | |
| dc.date.accessioned | 2024-05-14T09:53:12Z | |
| dc.date.available | 2014-06-05T12:43:40Z | |
| dc.date.available | 2024-05-14T09:53:12Z | |
| dc.date.issued | 2013 | |
| dc.description | Magister Scientiae - MSc | en_US |
| dc.description.abstract | This thesis looks at the effect that the introduction of various techniques (weighting, bootstrapping and variable selection) has on the accuracy of the modelling process when using logistic regression. The data used in the modelling process is based on the sexual activity of entering first-year students at the University of the Western Cape, therefore, by constructing logistic regression models based on this data, certain predictor variables or factors associated with the sexual activity of these students are identified. The sample weighting technique utilized in this thesis assigned a weight to a student based on gender and racial representations within a sample when compared to the population of the entering first-year. The use of a sample weighting technique is shown to produce a more effective modelling process than a modelling process without weighting. The bootstrapping procedure is shown to produce logistic regression models that are more accurate. Utilizing more than 200 bootstrap samples did not necessarily produce logistic regression models that were more accurate than using a total of 200 bootstrap samples. It is, however, concluded that a weighted bootstrap modelling procedure will result in more accurate models compared to a procedure without this intervention. The forward, backward, stepwise, Newton-Raphson and Fisher variable selection methods are used. The Newton-Raphson and Fisher methods are found not to be effective when used in a logistic modelling process, whereas the forward, backward and stepwise methods are all shown to produce very similar results. Six predictor variables or factors are identified with respect to the sexual activity of the specified students: the age of the student; whether they consume alcohol or not; their racial grouping; whether an HIV test has been taken; the importance of religion in influencing their sexual behaviour; and whether they smoke or not.i i Conclusions are reached with respect to improvements that could be made to the HIV prevention programme at UWC with reference to the sexual activity of entering first-years. | en_US |
| dc.identifier.uri | https://hdl.handle.net/10566/14895 | |
| dc.language.iso | en | en_US |
| dc.rights.holder | uwc | en_US |
| dc.subject | Sexual risk behaviour | en_US |
| dc.subject | Logistic regression | en_US |
| dc.subject | Variable selection | en_US |
| dc.subject | Weighted bootstrap | en_US |
| dc.subject | Sample weighting | en_US |
| dc.subject | HIV prevention | en_US |
| dc.subject | Alcohol | en_US |
| dc.subject | Smoking | en_US |
| dc.subject | Importance of religion | en_US |
| dc.subject | Sexually active | en_US |
| dc.title | Using a weighted bootstrap approach to identify risk factors associated with the sexual activity of entering first-year students at UWC | en_US |