Kurskatalog forskarutbildning  HT18

Startsida
Ansökan kan ske mellan 20180416 och 20180515
Application closed
Skriv ut
Skriv ut
Titel  Biostatistics III: Survival analysis for epidemiologists 

Kursnummer  2992 
Program  Epidemiologi 
Språk  Engelska 
Antal högskolepoäng  1.5 
Noteringar 
Kursen uppfyller kraven för en allmänvetenskaplig kurs. 
Datum  20171113  20171121 
Kursansvarig institution  Institutionen för medicinsk epidemiologi och biostatistik 
Särskild behörighet  Epidemiology I, Introduction to epidemiology; Biostatistics I, Introduction for epidemiologists; Biostatistics II, Logistic regression for epidemiologists or equivalent courses. 
Kursens syfte  This course focuses on the application of survival analysis methods to epidemiological studies. 
Kursens lärandemål  After successfully completing this course students should be able to:
 propose a suitable statistical model for assessing a specific research hypothesis using data from a cohort study, fit the model using standard statistical software, evaluate the fit of the model, and interpret the results.  explain the similarities and differences between Cox regression and Poisson regression.  discuss the concept of timescales in statistical models for timetoevent data, be able to control for different timescales using standard statistical software, and argue for an appropriate timescale for a given research hypothesis. discuss the concept of confounding in epidemiological studies and be able to control/adjust for confounding using statistical models.  apply and interpret appropriate statistical models for studying effect modification and be able to reparameterise a statistical model to estimate appropriate contrasts.  critically evaluate the methodological aspects (design and analysis) of a scientific article reporting a cohort study. 
Kursens innehåll  This course introduces statistical methods for survival analysis with emphasis on the application of such methods to the analysis of epidemiological cohort studies. Topics covered include methods for estimating survival (life table and KaplanMeier methods), comparing survival between subgroups (logrank test), and modelling survival (primarily Poisson regression and the Cox proportional hazards model). The course addresses the concept of 'time' as a potential confounder or effect modifier and approaches to defining 'time' (e.g., time since entry, attained age, calendar time). The course will emphasise the basic concepts of statistical modelling in epidemiology, such as controlling for confounding and assessing effect modification. 
Arbetsformer  Lectures, exercises focusing on analysis of real data using the free statistical software R, exercises not requiring statistical software, group discussions, literature review. 
Obligatoriska moment  The individual examination 
Examination  The course grade is based solely on a takehome examination. The focus of the exam will be on understanding concepts and their application to analysis of epidemiological studies rather than mathematical detail. The course examination will be held within two weeks of the final day of the course. Students who do not obtain a passing grade in the first examination will be offered a second examination within 2 months of the final day of the course. Students who do not obtain a passing grade at the first two examinations will be given top priority for admission the next time the course is offered. If the course is not offered during the following two academic terms then a third examination will be scheduled within 12 months of the final day of the course. 
Kurslitteratur och övriga läromedel  We have not assigned any compulsory texts since experience has shown that course participants have widely varying preferences. We will provide extensive course notes and many participants do not find a great need for additional texts. A large number of textbooks are available and we suggest students interested in additional reading to identify a textbook at a technical level suitable for them. Many general textbooks in medical statistics contain a chapter on survival analysis. This course has a heavy emphasis on application rather than theory; although the course software is R users of other software packages may prefer a textbook specifically designed for users of that software. Very few books are targeted at epidemiologists (e.g., you won't find Poisson regression mentioned in many books). The definitive text for epidemiologists is Breslow and Day (1987) although it is rather advanced. Suggested course literature: Cleves M et al. An Introduction to Survival Analysis Using Stata, 3rd edition. College Station: Stata Press; 2010. Breslow NE, Day NE. Statistical Methods in Cancer Research: The Design and Analysis of Cohort Studies. Lyon: IARC Scientific Publication; 1987. Free to download from http://www.iarc.fr/en/publications/pdfsonline/stat/sp82/index.php 
Antal studenter  8  25 
Urval av studenter  Eligible doctoral students, with required prerequisite knowledge, will be selected based on 1) the relevance of the syllabus for the applicant's doctoral project (according to written motivation), and 2) date for registration as doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a description of current research and motivation for attending, and an account of previous courses taken. 
Övrig information  The course will be held November 13, 15, 17, 20 and 21. The course is extended over two weeks (but still 5 course days) to promote reflection and active learning. The statistical software R will be used throughout the course. It is strongly recommended to have taken an introductory course in R or to have equivalent experience prior to taking this course. We have provided a selfassessment test (http://biostat3.net) for you to confirm that you understand the central concepts. We advise all potential applicants to take the test prior to applying for Biostatistics III. If you attempt the test under examination conditions (i.e., without referring to the answers) we would recommend: 1. if you score 70% or more then you possess the required prerequisite knowledge 2. if you score 40% to 70% you should revise the areas where you lost marks 3. if you score less than 40% you should, at a minimum, undertake an extensive review of central concepts in statistical modelling and possibly consider studying intermediate level courses (e.g., Biostatistics II) before taking Biostatistics III. 
Ytterligare kursledare  
Tidigare omdöme av kursen  omdöme 
Kursansvarig 
Mark Clements Institutionen för medicinsk epidemiologi och biostatistik mark.clements@ki.se 
Kontaktpersoner 
Gunilla Nilsson Roos Institutionen för medicinsk epidemiologi och biostatistik 08524 822 93 gunilla.nilsson.roos@ki.se 