The Epistemology behind Covariate Adjustment

TL;DR

This paper explores the epistemological debate on whether confounder effects can be controlled through statistical adjustment or only by experimental design, resolving a longstanding conundrum in causal inference.

Contribution

It provides a philosophical and methodological clarification on the conditions under which covariate adjustment can validly control for confounders without fallacious reasoning.

Findings

Clarifies the epistemological basis of covariate adjustment

Resolves the conundrum between statistical control and experimental design

Provides guidelines for valid confounder control in causal analysis

Abstract

It is often asserted that to control for the effects of confounders, one should include the confounding variables of concern in a statistical model as a covariate. Conversely, it is also asserted that control can only be concluded by design, where the results from an analysis can only be interpreted as evidence of an effect because the design controlled for the cause. To suggest otherwise is said to be a fallacy of cum hoc ergo propter hoc. Obviously, these two assertions create a conundrum: How can the effect of confounder be controlled for with analysis instead of by design without committing cum hoc ergo propter hoc? The present manuscript answers this conundrum.