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Joint modeling of longitudinal and time to event data with application to tuberculosis research
Mini Dissertation ( MSc (Advanced Data Analytics))--University of Pretoria, 2021.
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| Other Authors: | |
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2021
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| _version_ | 1867613683897597952 |
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| access_status_str | Open Access |
| author2 | Burger, Divan A. |
| author_browse | Burger, Divan A. |
| author_facet | Burger, Divan A. |
| collection | Thesis |
| dc_rights_str_mv | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Mini Dissertation ( MSc (Advanced Data Analytics))--University of Pretoria, 2021. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/78510 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:40:02.981Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/78510 Joint modeling of longitudinal and time to event data with application to tuberculosis research Burger, Divan A. snigrini1@gmail.com Nigrini, Sharday UCTD Tuberculosis Longitudinal Joint modeling Time-to-event Colony-forming-unit Mini Dissertation ( MSc (Advanced Data Analytics))--University of Pretoria, 2021. Due to tuberculosis (TB) being one of the top ten diseases in Africa with the highest mortality rate, a crucial objective is to find the appropriate medication to cure patients and prevent people from contracting the disease. Since this statistic is not improving sufficiently, it is evident that there is a need for new anti-TB drugs. One of the main challenges in developing new and effective drugs for the treatment of TB is to identify the combinations of effective drugs when subsequent testing of patients in pivotal clinical trials are performed. During the early weeks of the treatment of TB, trials of the early bactericidal activity assess the decline in colony-forming unit (CFU) count of Mycobacterium TB in the sputum of patients containing smear-microscopy-positive pulmonary TB. A previously published dataset containing CFU counts of treated patients over 56 days is used to perform joint modeling of the nonlinear data over time and the patients’ sputum culture conversion (i.e., the time-to-event outcome). It is clear from the results obtained that there is an association between the longitudinal and time-to-event outcomes. South African Medical Research Council (SAMRC) Statistics MSc (Advanced Data Analytics) Restricted 2021-02-12T09:51:04Z 2021-02-12T09:51:04Z 2021-05-05 2021 Mini Dissertation * A2021 http://hdl.handle.net/2263/78510 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Tuberculosis Longitudinal Joint modeling Time-to-event Colony-forming-unit Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title | Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title_full | Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title_fullStr | Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title_full_unstemmed | Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title_short | Joint modeling of longitudinal and time to event data with application to tuberculosis research |
| title_sort | joint modeling of longitudinal and time to event data with application to tuberculosis research |
| topic | UCTD Tuberculosis Longitudinal Joint modeling Time-to-event Colony-forming-unit |
| url | http://hdl.handle.net/2263/78510 |