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The curriculum builds from survival analysis foundations to advanced themes including beyond the Cox model, multivariate survival analysis, competing risk and multistate models, and interval censoring. It specifies required prior skills, practical laboratory work using R, and a continuous evaluation grading scheme across Blocks B1–B4.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":20,"@type":76,"position":81},"https://docshare.wps.com/document/exam/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/200629-asa-advanced-topics-in-survival-analysis/387904/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/200629-asa-advanced-topics-in-survival-analysis/387904.png","ImageObject",300,407,{"name":92,"@type":93},"percent12345","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What prior skills are required before taking the course?","Question",{"text":112,"@type":113},"Students must know core survival analysis concepts such as censored data, likelihood with censoring, Kaplan-Meier estimator, log-rank test, accelerated failure time and Cox proportional hazards models, and diagnostics for Cox regression.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What are the main learning objectives of the subject?",{"text":117,"@type":113},"The course prepares students to handle complex censoring patterns, time-varying covariates, multivariate analysis for events at two or more times, and multistate models.",{"name":119,"@type":110,"acceptedAnswer":120},"How is student performance evaluated?",{"text":121,"@type":113},"Blocks B1, B2, B3, and B4 are evaluated independently with grades N1–N4, and the final course grade NF is their average: NF = (N1 + N2 + N3 + N4)/4.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},387904,1792212683,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":19,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":52,"preview_page_count":4},1099529851338,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Course guide  \n200629 -ASA -Advanced Topics in Survival Analysis  \nLast modified: 22/05/2022  \nUnit in charge: School of Mathematics and Statistics  \nTeaching unit: 715-EIO-Department of Statistics and Operations Research.  \nDegree: MASTER'S DEGREE IN STATISTICS AND OPERATIONS RESEARCH (Syllabus 2013) . (Optional subject) .  \nAcademic year: 2022 ECTS Credits: 5.0 Languages: English  \nLECTURER  \n\n| Coordinating lecturer: GUADALUPE GÓMEZ MELIS\u003Cbr>Others: Segon quadrimestre:\u003Cbr>GUADALUPE GÓMEZ MELIS-A\u003Cbr>KLAUS GERHARD LANGOHR-A\u003Cbr>PRIOR SKILLS |\n| --- |\n| Students must know the basic concepts of survival analysis These concepts include: Censored data, Likelihood in the presence of censoring, Continuous parametric distributions other than normal, Kaplan-Meier survival estimator, Log-rank test, Accelerated Failure Time Model, Cox proportional hazards model and Diagnostic of the Cox Regression model. The student can find these concepts in chapters 2-4, 7-8, 11-12 in the book \"Survival analysis: techniques for censored and truncated data\" by Klein and Moeschberger. These topics could have been self-learnt, in the first semester Lifetime Data Analysis course or in other undergraduate or postgraduate courses.\u003Cbr>DEGREE COMPETENCES TO WHICH THE SUBJECT CONTRIBUTES |\n\nSpecific:  \n1. CE-1 . Ability to design and manage the collection of information and coding, handling, storing and processing it.  \n2. CE-2 . Ability to master the proper terminology in a field that is necessary to apply statistical or operations research models and methods to solve real problems.  \n3. CE-3 . Ability to formulate, analyze and validate models applicable to practical problems. Ability to select the method and / or statistical or operations research technique more appropriate to apply this model to the situation or problem.  \n4. CE-4 . Ability to use different inference procedures to answer questions, identifying the properties of different estimation methods and their advantages and disadvantages, tailored to a specific situation and a specific context.  \n5. CE-5 . Ability to formulate and solve real problems of decision-making in different application areas being able to choose the statistical method and the optimization algorithm more suitable in every occasion.  \nTranslate to english  \n6. CE-6 . Ability to use appropriate software to perform the necessary calculations in solving a problem.  \n7. CE-7 . Ability to understand statistical and operations research papers of an advanced level. Know the research procedures for both the production of new knowledge and its transmission.  \nTransversal:  \n8. TEAMWORK: Being able to work in an interdisciplinary team, whether as a member or as a leader, with the aim of contributing to projects pragmatically and responsibly and making commitments in view of the resources that are available.  \n9. EFFECTIVE USE OF INFORMATION RESOURCES: Managing the acquisition, structuring, analysis and display of data and information in the chosen area of specialisation and critically assessing the results obtained.  \nTEACHING METHODOLOGY  \nLectures are organized into two types:  \na) Theoretical sessions in which the teacher presents and discusses the general learning objectives and basic concepts. These concepts are motivated with real case studies. The support material used will be published in advance in Atenea (syllabus, content, slides, examples, scheduled assessment activities, references, ...)  \nStudents will give a presentation of their own data (if any) if related with the contents of the course.  \nb) Laboratory classes. These sessions focus on the practical aspects of the methodology. Software R is available for the students and they can continue laboratory sessions in their hours of self study.  \nStudents must devote enough time to complement the lectures by reading research papers, solving problems, learning relevant software, etc.  \nLEARNING OBJECTIVES OF THE SUBJECT  \nThe course Advanced Survival Analysis prepares students ","cbCail9nEfI0nSq7","https://ap.wps.com/l/cbCail9nEfI0nSq7","pdf",81475,"English","# Prior Skills\n# Degree Competences\n## Specific\n## Transversal\n# Teaching Methodology\n# Learning Objectives of the Subject\n# Study Load\n# Contents\n## B1: Beyond the Cox Model\n## B2: Multivariate Survival Analysis\n## B3: Competiting Risk Analysis and Multistate Models\n## B4: Interval Censoring\n# Grading System","[{\"question\":\"What prior skills are required before taking the course?\",\"answer\":\"Students must know core survival analysis concepts such as censored data, likelihood with censoring, Kaplan-Meier estimator, log-rank test, accelerated failure time and Cox proportional hazards models, and diagnostics for Cox regression.\"},{\"question\":\"What are the main learning objectives of the subject?\",\"answer\":\"The course prepares students to handle complex censoring patterns, time-varying covariates, multivariate analysis for events at two or more times, and multistate models.\"},{\"question\":\"How is student performance evaluated?\",\"answer\":\"Blocks B1, B2, B3, and B4 are evaluated independently with grades N1–N4, and the final course grade NF is their average: NF = (N1 + N2 + N3 + N4)/4.\"}]","200629 -ASA -Advanced Topics in Survival Analysis | PDF",1790290893]