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Title | Extensions to the Design and Analysis of Controlled Epidemiological Studies |
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Course number | 5577 |
Programme | Epidemiologi |
Language | English |
Credits | 1.5 |
Date | 2022-11-16 -- 2022-11-25 | Responsible KI department | Institutionen för medicinsk epidemiologi och biostatistik |
Specific entry requirements | Epidemiology I, Introduction to epidemiology; Epidemiology II, Design of epidemiological studies; Biostatistics I, Introduction for epidemiologists; Biostatistics II, Logistic regression for epidemiologists; and Biostatistics III: Survival analysis for epidemiologists, or equivalent courses |
Purpose of the course | This course aims to enable practicing epidemiologists to make more efficient use of already-available epidemiological data, and to design studies that are more efficient and that will extend possibilities for future analysis. |
Intended learning outcomes | After successfully completing this course you as a student are expected to be able to:
- select a suitable epidemiological design for addressing a specified research question and justify the choice of design compared to other options. - compare the risk estimates obtained by different sampling strategies from the same underlying cohort and interpret these estimates for common designs. - compare and contrast the purpose of time-matching and confounder-matching in (nested) case-control studies, and generalise the resulting risk sets to a wide range of standard and non-standard designs. - compute weights that enable the reconstruction of an underlying study base from a (nested) case-control sample and recognise that two-stage designs, extended/extreme designs and reused case-control data, can all be analysed using appropriate weights to reflect the sampling - discuss the designs of published studies with particular attention to the choice of controls and devise more efficient alternatives. |
Contents of the course | The overall aim of this course is to present more flexible and informative approaches to the design and analysis of epidemiological studies, in order to make efficient use of costly data. The course will introduce methods for designing more efficient studies that exploit available population data and/or reuse data from prior studies conducted in well-defined cohorts (such as national registers). The focus will be on different sampling designs in terms of their (biased) representation of the underlying cohort, and how to reconstruct the correct numbers at-risk to produce unbiased parameter estimates, including several important quantities (other than the odds ratio). The course will demonstrate how (i) extended efficient designs can be analysed with standard methods, and (ii) extended methods of analysis can provide additional estimates from standard designs. |
Teaching and learning activities | Lectures interspersed with tutorials consisting of workshops and journal club sessions. In the workshops, participants will develop and refine a study design to address a clinical/epidemiological research question which will be presented and discussed. Journal clubs will consist of discussion and debate concerning key papers that will be assigned. |
Compulsory elements | The individual examination |
Examination | The course grade will be based on a take-home assignment involving a proposed epidemiological study. The participant will submit a short, written report and an oral presentation where they will present and defend their proposal. A passing grade must be obtained for both the written and oral section in order to obtain a passing grade for the course. Students who do not obtain a passing grade on one of these sections will be allowed to revise that part of their work and be re-examined under the same conditions. The exam will have a strong emphasis on intuitive understanding and ability to explain/communicate rather than on technical or mathematical detail. The take-home examination will be explained on the first day of the course, assigned on the last day, and due within ten days of the end 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. |
Literature and other teaching material | Suggested course literature:
The course is based on a text book in preparation by the instructor, involving material from several decades of scientific publications concerning epidemiological designs. All participants will be asked to read Chapters 1, 2 and 4 (assumed to be familiar material) before the course, together with the key papers 1-5 below. The course material will be based mostly on Chapters 6-9 of the draft text book and related key papers. Teaching material will also consist of Stata and R code that enables the implementation of the methods introduced in the laboratory sessions. 1. Vandenbroucke JP, Pearce N. Case-control studies: basic concepts. Int J Epidemiol. 2012 Oct;41(5):1480-9. 2. Knol MJ, Vandenbroucke JP, Scott P, Egger M. What do case-control studies estimate? Survey of methods and assumptions in published case-control research. Am J Epidemiol. 2008 Nov 1;168(9):1073-81. 3. Borgan O, Samuelsen SO. A review of cohort sampling designs for Cox regression model: potentials in epidemiology. Norsk Epi. 2003, 13(2), 239-248. 4. Hanley J and Foster B. Avoiding blunders involving “immortal time”. Int Jour Epi. 2014, 43:949–961 5. Kim RS. A new comparison of nested case-control and case-cohort designs and methods. Eur J Epidemiol., 30:197-207, 2015. 6. Suissa S. The Quasi-cohort approach in pharmacoepidemiology: upgrading the nested case-control. Epidemiology. 2015 Mar;26(2):242-6. 7. Delcoigne B, et al. Feasability of reusing time-matched controls in an overlapping cohort. Stat Meth Med Res 2018, 27(6) 1818-1829. 8. Keogh RH, et al. Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses. BMC Med Res Methodol. 2016, 16:2. doi: 10.1186/s12874-015-0104-0. 9. Heller RF et al. Impact numbers: measures of risk factor impact on the whole population from case-control and cohort studies. J Epidemiol Community Health. 2002, 56(8):606-610. 10. Arnold BF et al. Brief Report: Negative Controls to Detect Selection Bias and Measurement Error in Epidemiologic Studies. Epidemiology 2016, 27(5):637-41. |
Number of students | 8 - 25 |
Selection of students | Eligible doctoral students will be prioritized according to 1) the relevance of the course syllabus for the applicant’s doctoral project (according to written information), 2) date for registration as a doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a short description of current research training and motivation for attending, as well as an account of previous courses taken. |
More information | The course is extended over time in order to promote reflection and reinforce learning. The course will be held the dates November 16, 18, 21, 23 and 25. |
Additional course leader | |
Latest course evaluation | Course evaluation report |
Course responsible |
Marie Reilly Institutionen för medicinsk epidemiologi och biostatistik 08-524 839 82 Marie.Reilly@ki.se |
Contact person |
Gunilla Nilsson Roos Institutionen för medicinsk epidemiologi och biostatistik 08-524 822 93 gunilla.nilsson.roos@ki.se |
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