Negative Controls
Center for Disease Dynamics, Economics & Policy · Harvard University · +1 more institution
Abstract
Noncausal associations between exposures and outcomes are a threat to validity of causal inference in observational studies. Many techniques have been developed for study design and analysis to identify and eliminate such errors. Such problems are not expected to compromise experimental studies, where careful standardization of conditions (for laboratory work) and randomization (for population studies) should, if applied properly, eliminate most such noncausal associations. We argue, however, that a routine precaution taken in the design of biologic laboratory experiments--the use of "negative controls"--is designed to detect both suspected and unsuspected sources of spurious causal inference. In epidemiology,…
Citation impact
- FWCI
- 12.52
- Percentile
- 100%
- References
- 29
Authors
3Topics & keywords
- Observational study
- Confounding
- Causal inference
- Spurious relationship
- Inference
- Population
- Clinical study design
- Type I and type II errors
- Good health and well-being