{"id":4519,"date":"2025-05-15T13:11:29","date_gmt":"2025-05-15T11:11:29","guid":{"rendered":"https:\/\/www.escience.ac.za\/?p=4519"},"modified":"2025-05-15T13:11:30","modified_gmt":"2025-05-15T11:11:30","slug":"a-new-frontier-pseudo-observations-role-in-survival-analysis","status":"publish","type":"post","link":"https:\/\/www.escience.ac.za\/index.php\/2025\/05\/15\/a-new-frontier-pseudo-observations-role-in-survival-analysis\/","title":{"rendered":"A New Frontier: Pseudo-Observation&#8217;s Role in Survival Analysis"},"content":{"rendered":"<p><strong>Researcher<\/strong>: Kgoale Tshiamo Mahlako<br><strong>Supervisor<\/strong>: Dr A Whata<\/p><p>Survival analysis is a vital field in statistics, offering valuable insights into various domains, from healthcare to epidemiology. It allows us to understand the factors that influence time-to-event outcomes. The analysis of survival data comes with its own set of challenges, especially when it involves censoring.<br>Censoring occurs when we don\u2019t have complete information about the event times, making it difficult to draw causal inferences. The application of pseudo-observations, which is a crucial tool for enhancing causal inference, will be the subject of our particular attention. We apply the G-formula and IPTW, methods from causal inference, on these pseudo-observations. And estimate the ATE for a completely observed outcome and censored data.<\/p><p><\/p><div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"731\" height=\"1024\" src=\"https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-731x1024.jpg\" alt=\"\" class=\"wp-image-4520\" srcset=\"https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-731x1024.jpg 731w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-214x300.jpg 214w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-768x1075.jpg 768w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-1097x1536.jpg 1097w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-1463x2048.jpg 1463w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-600x840.jpg 600w, https:\/\/www.escience.ac.za\/wp-content\/uploads\/2025\/05\/2187338516-Tshiamo-Kgoale-41426_Tshiamo_Kgoale_tshiamo_poster_18079_1786076107-scaled.jpg 1829w\" sizes=\"(max-width: 731px) 100vw, 731px\" \/><\/figure><\/div><p>&nbsp;<\/p>","protected":false},"excerpt":{"rendered":"<p>Researcher: Kgoale Tshiamo MahlakoSupervisor: Dr A Whata Survival analysis is a vital field in statistics, offering valuable insights into various domains, from healthcare to epidemiology. It allows us to understand the factors that influence time-to-event outcomes. The analysis of survival data comes with its own set of<\/p>\n","protected":false},"author":3,"featured_media":4494,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-4519","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-capstone-projects"],"_links":{"self":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/4519","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/comments?post=4519"}],"version-history":[{"count":1,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/4519\/revisions"}],"predecessor-version":[{"id":4521,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/4519\/revisions\/4521"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media\/4494"}],"wp:attachment":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media?parent=4519"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/categories?post=4519"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/tags?post=4519"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}