  Experimental and observational studies often lead to spurious association
between the outcome and independent variables describing the intervention,
because of confounding to third-party factors. Even in randomized clinical
trials, confounding might be unavoidable due to small sample sizes.
Practically, this poses a problem, because it is either expensive to re-design
and conduct a new study or even impossible to alleviate the contribution of
some confounders due to e.g. ethical concerns. Here, we propose a method to
consistently derive hypothetical studies that retain as many of the
dependencies in the original study as mathematically possible, while removing
any association of observed confounders to the independent variables. Using
historic studies, we illustrate how the confounding-free scenario re-estimates
the effect size of the intervention. The new effect size estimate represents a
concise prediction in the hypothetical scenario which paves a way from the
original data towards the design of future studies.
