{"id":{"repo_id":"freiburg-diss","oai_identifier":"oai:freidok.uni-freiburg.de:1843"},"canonical_url":"https://search.dev.ndltd.org/etd/freiburg-diss/oai:freidok.uni-freiburg.de:1843","repository":{"repo_id":"freiburg-diss","name":"University of Freiburg","base_url":"https://freidok.uni-freiburg.de/oai/oai2.php"},"display":{"title":"On change in length of stay associated with an intermediate event: estimation within multi-state models and large sample properties","abstract":"This thesis is on the impact of an intermediate on a terminal event. <br>More precisely, it is concerned with quantifying such an impact in <br>terms of (expected) change in length of stay until occurrence of the <br>terminal and associated with the intermediate event. Essentially, we <br>treat the situation as a random time interval problem, with length of <br>the time interval (possibly zero) equal to the time spent in the <br>intermediate state. We suggest and study functionals quantifying <br>change in length of stay. Our approach applies quite generally to <br>functionals summarizing the impact of an intermediate on a terminal <br>event.","abstract_html":"This thesis is on the impact of an intermediate on a terminal event. &lt;br&gt;More precisely, it is concerned with quantifying such an impact in &lt;br&gt;terms of (expected) change in length of stay until occurrence of the &lt;br&gt;terminal and associated with the intermediate event. Essentially, we &lt;br&gt;treat the situation as a random time interval problem, with length of &lt;br&gt;the time interval (possibly zero) equal to the time spent in the &lt;br&gt;intermediate state. We suggest and study functionals quantifying &lt;br&gt;change in length of stay. Our approach applies quite generally to &lt;br&gt;functionals summarizing the impact of an intermediate on a terminal &lt;br&gt;event.","abstract_has_math":false,"creators":["Beyersmann, Jan"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Schumacher, Martin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T02:22:28Z","subjects":["biometry","multistate model","nosocomial infection","random time interval"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://freidok.uni-freiburg.de/data/1843","outbound_label":"Repository record","outbound_source":"source_url"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Schumacher, Martin"]},{"key":"dc:creator","label":"Author","values":["Beyersmann, Jan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["DoctoralThesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["biometry","multistate model","nosocomial infection","random time interval"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis is on the impact of an intermediate on a terminal event. <br>More precisely, it is concerned with quantifying such an impact in <br>terms of (expected) change in length of stay until occurrence of the <br>terminal and associated with the intermediate event. Essentially, we <br>treat the situation as a random time interval problem, with length of <br>the time interval (possibly zero) equal to the time spent in the <br>intermediate state. We suggest and study functionals quantifying <br>change in length of stay. Our approach applies quite generally to <br>functionals summarizing the impact of an intermediate on a terminal <br>event.","Diese Arbeit behandelt die Auswirkung eines intermediären auf ein <br>terminales Ereignis. Genauer: Ziel ist es, die Auswirkung mittels der <br>(erwarteten) Änderung der Aufenthaltsdauer bis zum Eintreten des <br>terminalen und nach Eintreten des intermediären Ereignisses zu <br>quantifizieren. Unser wesentlicher Ansatz ist es, diese Situation als <br>ein zufälliges Zeitintervall-Problem zu beschreiben, dessen Länge <br>(möglicherweise Null) der Aufenthaltsdauer im intermediären Zustand <br>entspricht. Wir schlagen Funktionale vor, die die Änderung der <br>Aufenthaltsdauer quantifizieren, und analysieren diese. Unser Ansatz <br>ist allgemein geeignet zur Behandlung von Funktionalen, die die <br>Auswirkung eines intermediären auf ein terminales Ereignis <br>zusammenfassend beschreiben."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["On change in length of stay associated with an intermediate event: estimation within multi-state models and large sample properties","Zur Änderung der Aufenthaltsdauer nach einem intermediären Ereignis: Schätzung innerhalb von Mehrstadienmodellen und Eigenschaften für große Stichproben"]}]}],"canonical_facts":{"dc:contributor":["Schumacher, Martin"],"dc:creator":["Beyersmann, Jan"],"dc:description.abstract":["This thesis is on the impact of an intermediate on a terminal event. <br>More precisely, it is concerned with quantifying such an impact in <br>terms of (expected) change in length of stay until occurrence of the <br>terminal and associated with the intermediate event. Essentially, we <br>treat the situation as a random time interval problem, with length of <br>the time interval (possibly zero) equal to the time spent in the <br>intermediate state. We suggest and study functionals quantifying <br>change in length of stay. Our approach applies quite generally to <br>functionals summarizing the impact of an intermediate on a terminal <br>event.","Diese Arbeit behandelt die Auswirkung eines intermediären auf ein <br>terminales Ereignis. Genauer: Ziel ist es, die Auswirkung mittels der <br>(erwarteten) Änderung der Aufenthaltsdauer bis zum Eintreten des <br>terminalen und nach Eintreten des intermediären Ereignisses zu <br>quantifizieren. Unser wesentlicher Ansatz ist es, diese Situation als <br>ein zufälliges Zeitintervall-Problem zu beschreiben, dessen Länge <br>(möglicherweise Null) der Aufenthaltsdauer im intermediären Zustand <br>entspricht. Wir schlagen Funktionale vor, die die Änderung der <br>Aufenthaltsdauer quantifizieren, und analysieren diese. Unser Ansatz <br>ist allgemein geeignet zur Behandlung von Funktionalen, die die <br>Auswirkung eines intermediären auf ein terminales Ereignis <br>zusammenfassend beschreiben."],"dc:format.medium":["application/pdf"],"dc:subject":["biometry","multistate model","nosocomial infection","random time interval"],"dc:title":["On change in length of stay associated with an intermediate event: estimation within multi-state models and large sample properties","Zur Änderung der Aufenthaltsdauer nach einem intermediären Ereignis: Schätzung innerhalb von Mehrstadienmodellen und Eigenschaften für große Stichproben"],"dc:type":["DoctoralThesis"]},"updated_at":"2026-07-24T02:22:28Z"}