Designs combining instrumental variables with case-control: Estimating principal strata causal effects

Russell T. Shinohara, Constantine E. Frangakis, Elizabeth Platz, Konstantinos Tsilidis

Research output: Contribution to journalArticle


The instrumental variables framework is commonly used for the estimation of causal effects from cohort samples. However, the combination of instrumental variables with more efficient designs such as case-control sampling requires new methodological consideration. For example, as the use of Mendelian randomization studies is increasing and the cost of genotyping and gene expression data can be high, the analysis of data gathered from more cost-effective sampling designs is of prime interest. We show that the standard instrumental variables analysis does not appropriately estimate the causal effects of interest when the instrumental variables design is combined with the case-control design. We also propose a method that can estimate the causal effects in such combined designs. We illustrate the method with a study in oncology.

Original languageEnglish (US)
Article number2
JournalInternational Journal of Biostatistics
Issue number1
StatePublished - Mar 7 2012



  • Case-control
  • Instrumental variables
  • Mendelian randomization
  • Principal stratification
  • Study design

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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