A quasi-experimental device is a data element that is added to an observational study in the hope that it will shed light on unmeasured confounding. The systematic study of quasi-experimental devices began in a paper published by Donald T. Campbell in 1957 in Psychological Bulletin 54(4):297-312 https://doi.org/10.1037/h0040950. With colleagues, Campbell published three books about quasi-experiments. Many commonly used quasi-experimental devices originate in the work of Donald Campbell and his colleagues, including multiple control groups, regression-discontinuity and difference-in-differences. Other quasi-experimental device are: (i) the use of known effects or placebo outcomes, (ii) the use of isolation, (iii) constructed second control groups, (iv) combining within and between institution comparisons, and (v) general forms of effect aliasing beyond difference-in-differences. For an informal discussion of quasi-experimental devices, see Chapter 6 of my book Causal Inference (MIT Press, 2023) or Chapter 8 of my book Observation and Experiment (Harvard University Press, 2017).
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Zubizarreta JR, Small DS, Rosenbaum PR. A simple example of isolation in building a natural experiment. Chance. 2018 Oct 2;31(4):16-23. https://doi.org/10.1080/09332480.2018.1549811
Rosenbaum PR. Sensitivity analyses informed by tests for bias in observational studies. Biometrics. 2023 Mar;79(1):475-87. https://doi.org/10.1111/biom.13558
Rosenbaum PR. Can we reliably detect biases that matter in observational studies?. Statistical Science. 2023 Aug;38(3):440-57. Open access in ProjectEuclid: https://doi.org/10.1214/23-STS882
Rosenbaum PR. Does a Daily Glass of Wine Lengthen Life? Insight from a Second Control Group. Chance. 2025 Jan 2;38(1):25-30. https://doi.org/10.1080/09332480.2025.2473291
Rosenbaum PR, Zubizarreta JR. Effect aliasing in observational studies. Journal of the American Statistical Association. 2026 Jan 2;121(553):624-35. https://doi.org/10.1080/01621459.2025.2537456