Extensions to the design and analysis of case-control studies

Doctoral course within the doctoral programme in Epidemiology
Course number: 2991
Credit points: 1,5


To enable practicing epidemiologists to make more efficient use of already-available case-control data and to design case-control studies that will extend the possibilities
for future analysis.

Learning outcome

After successfully completing this course, the student is 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 cohort from a (nested) case-control sample and recognise that two-stage designs, re-use of case-control data, and extended/extreme case-control designs 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 alternative designs.

Content of the course

The course will present statistical approaches that enable researchers to design more efficient case-control studies and to exploit more efficiently the data provided by nested case-control studies conducted in well-defined cohorts (such as national registers). In particular, the course will focus 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, include several important quantities (other than the odds ratio). The course will demonstrate the application of these methods to re-use controls from a prior study or after breaking the matching in a matched case-control study, conduct more flexible and informative analysis, and make efficient use of costly data.

Lectures will be 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 consists of discussion and debate concerning key papers that will be assigned.

Course Literature

As this is an advanced course, it is not covered in a text book, but involves material from several decades of scientific publications concerning case-control designs. For advance reading, the participants will be asked to re-read papers 1-5 below (with which they are assumed to be familiar), and to read papers 6-10 before the course.

  1. Miettinen O. Design options in epidemiologic research. An update. Scand J Work Environ Health. 1982;8 Suppl 1:7-14.
  2. Vandenbroucke JP, Pearce N. Case-control studies: basic concepts. Int J Epidemiol. 2012 Oct;41(5):1480-9.
  3. 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.
  4. Ernster VL. Nested case-control studies. Prev Med. 1994 Sep;23(5):587-90.
  5. Pearce N. Analysis of matched case-control studies. BMJ. 2016 Feb 25;352:i969.
  6. Borgan O, Samuelsen SO. A review of cohort sampling designs for Cox¿s regression model: potentials in epidemiology. Norsk Epi. 2003, 13(2), 239-248.
  7. Hanley JA. The Breslow estimator of the nonparametric baseline survivor function in Cox's regression model: some heuristics. Epidemiology. 2008 Jan;19(1):101-2.
  8. Heller RF, Dobson AJ, Attia J, Page J. Impact numbers: measures of risk factor impact on the whole population from case-control and cohort studies. J Epidemiol Community Health. 2002 Aug;56(8):606-10.
  9. Salim A, et al. A maximum likelihood method for secondary analysis of nested case-control data.Stat Med. 2014 May 20;33(11):1842-52.
  10. Arnold BF, Ercumen A, Benjamin-Chung J, Colford JM Jr. Brief Report: Negative Controls to Detect Selection Bias and Measurement Bias in Epidemiologic Studies. Epidemiology. 2016 ;27(5):637-41.

Course director and contact persons

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Marie Reilly

Professor Emeritus/Emerita
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Gunilla Nilsson Roos

Educational Administrator
Content reviewer: