Categories → Causal Inference , Validation , Statistics , Study Design
Adding a placebo treatment can help to establish whether a treatment has a genuine causal effect on an outcome or whether any observed effect is due to other factors.
NOTE: Please read this article for a detailed guide to refutation and statistical significance testing in DoWhy, a Python library used in Causal Wizard.
Refutation is a key concept in causal inference, which refers to the process of testing a hypothesis by attempting to prove it false. One way to do this is by using a placebo treatment.
Falsifying or refuting an outcome should not been seen as a disappointment:
Strict refutation helps to ensure - but does not guarantee - that results are sound and trustworthy.
A placebo treatment is a substance or procedure that has no active ingredients or therapeutic effect, but is designed to look and feel like a real treatment. It often has a measurable effect, simply due to participants' belief in the treatment!
By administering a placebo treatment to a group of subjects, researchers can create a control group that is identical to the treatment group in every way except for the absence of the active ingredient or therapeutic effect. In Causal Wizard, the placebo treatment cohort is achieved by randomly permuting the samples' Treated and Control cohort status, in place of the real groupings.
In the context of causal inference, the use of a placebo treatment can help to establish whether a treatment has a genuine causal effect on an outcome of interest, or whether any observed effect is due to other factors. Specifically, if the treatment group shows a statistically significant difference in the outcome compared to the placebo group, this suggests that the treatment does have a causal effect. On the other hand, if there is no statistically significant difference between the treatment and placebo groups, this suggests that the treatment does not have a causal effect, or that any observed effect is due to factors other than the treatment itself.
Therefore, adding a placebo treatment to a study can help researchers to establish whether a treatment has a causal effect on an outcome, or whether the observed effect is due to other factors. This process of refutation can strengthen the evidence for a causal relationship between a treatment and an outcome, and help to ensure that interventions are effective and safe.