Statistical Assessment of Malaria Risk Factors Using Cox Proportional Hazard Approach
Bibliographic Data
| ID | 5218455 |
|---|---|
| Authors | Ruffin Mutambayi (0000-0003-1758-6952, University of Fort Hare, corresponding author), James Ndege (University of Fort Hare), Adeboye Azeez (0000-0001-9427-7374, University of Fort Hare), Yong Song Qin (University of Fort Hare), Akinwumi Odeyemi (University of Fort Hare) |
| Year | 2017 |
| Volume | 60 |
| Issue | 2-3 |
| Pages | 106-116 |
| Publication date | 2017-12-02 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Human Ecology (JOURNAL) |
| Journal identifiers | ISSN: 0970-9274 • E-ISSN: 2456-6608 |
| Publisher | Kamla Raj Enterprises (PUBLISHER) |
| DOI | 10.1080/09709274.2017.1387368 |
| OpenAlex | W2793972436 |
| Language | EN |
| References cited | 18 |
The Cox proportional hazards (PH) model with time-dependent covariates has been widely used in medical and health related studies to examine the impacts of time-varying risk factors on survival. The study aimed to model the relapsing time using biographical, sanitation, environmental and preventive information as covariate risk factors. The Kaplan-Meier method, log-rank test and the Cox proportional hazards (PH) model to examining the covariates. The results indicates that the model h(t) = h0 (t)exp(1.91613Xdump - 0.49633Xspr + 0.81466Xinf1 ) was found to fit the data better, as confirmed by the result of the global test that present reasonable and significant results (Likelihood Ratio: 18.2264, p < 0.0004; Score: 17.6569, p < 0.0005 and Wald: 19.3975, p < 0.0002). In conclusion it was found that, ‘dumping site’ (p < 0.0106; 95% C.I: 1.545-29.451), ‘spray used’ (p < 0. 0.0220; 95% C.I: 0.391- 0 .915), and ‘information related to source of malaria’ (p < 0. 0.0012; 95% C.I: 1.380-3.725), have a significant effect on the relapsing time of patients under investigation
Biology · Econometrics · Hazard · Hazard ratio · Malaria · Proportional hazards model · Statistics · Advanced Statistical Methods and Models · Computational Drug Discovery Methods · Environmental Science · Imbalanced Data Classification Techniques · Mathematics · Medicine · Ecology · Immunology
| Citation velocity | historical |
|---|---|
| Highly cited | No |