{"id":8232,"date":"2025-09-15T23:03:19","date_gmt":"2025-09-15T23:03:19","guid":{"rendered":"https:\/\/medical-article.com\/?p=8232"},"modified":"2025-09-15T23:03:19","modified_gmt":"2025-09-15T23:03:19","slug":"what-is-the-difference-between-a-markov-and-semi-markov-model","status":"publish","type":"post","link":"https:\/\/medical-article.com\/?p=8232","title":{"rendered":"What is the difference between a Markov and semi-Markov model?"},"content":{"rendered":"<p>The free online book <em><a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/chapters\/10.markov_models\/markov-models#sec-markov_vs_semimarkov\">R for Health Technology Assessment<\/a><\/em> has the answer:<\/p>\n<p>Markov models are characterised by a memoryless property called the Markov assumption or Markov property. Under the Markov assumption, movement of an individual from their current health state to a future one, conditional on both past and current health states, depends only on the current health state of the individual and not the past health states (<a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/references#ref-Jackson2011a\">Jackson, 2011<\/a>;\u00a0<a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/references#ref-Kalbfleisch2002\">Kalbfleisch and Prentice, 2002<\/a>). A\u00a0<strong>semi-Markov<\/strong>\u00a0model relaxes this assumption so that transition rates can also depend on the\u00a0<strong>sojourn<\/strong>\u00a0time, which is the time spent in the current state. In this sense, a semi-Markov model is a\u00a0<strong>clock-reset<\/strong>\u00a0model\u00a0(<a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/references#ref-Green2023\">Green et al., 2023<\/a>;\u00a0<a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/references#ref-MeiraMachado2009\">Meira-Machado et al., 2009<\/a>). Time in a Markov model is defined as time since initiation of the model, so is termed\u00a0<strong>clock-forward<\/strong>. Markov and semi-Markov models are both examples of multistate models\u2026<\/p>\n<p>The <em><a href=\"https:\/\/gianluca.statistica.it\/books\/online\/r-hta\/\">R for Health Technology Assessment<\/a><\/em> has lots of details on to use R to not only creates both types of Markov models, but also decision trees, discrete event simulations, network meta-analyses and more.  A great resource for the field. <\/p>","protected":false},"excerpt":{"rendered":"<p>The free online book R for Health Technology Assessment has the answer: Markov models are characterised by a memoryless property called the Markov assumption or Markov property. Under the Markov assumption, movement of an individual from their current health state to a future one, conditional on both past and current health states, depends only on&#8230;<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-8232","post","type-post","status-publish","format-standard","hentry","category-articles"],"_links":{"self":[{"href":"https:\/\/medical-article.com\/index.php?rest_route=\/wp\/v2\/posts\/8232"}],"collection":[{"href":"https:\/\/medical-article.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/medical-article.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/medical-article.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8232"}],"version-history":[{"count":0,"href":"https:\/\/medical-article.com\/index.php?rest_route=\/wp\/v2\/posts\/8232\/revisions"}],"wp:attachment":[{"href":"https:\/\/medical-article.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8232"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medical-article.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8232"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medical-article.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8232"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}