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Residual confounding is challenging to detect. Recently, we described a method for detecting confounding and justified it primarily for time-series studies. The method depends on an indicator with 2 key characteristics: (1) it is conditionally independent (given measured exposures and covariates) of the outcome, in the absence of confounding, misspecification, and measurement errors; and (2) like the exposure, it is associated with confounders, possibly unmeasured. We proposed using future exposure levels as the indicator to detect residual confounding. This choice seems natural for time-series studies because future exposure cannot have caused the event, yet they could be spuriously related to it. A related question addressed here is whether an analogous indicator can be used to identify residual confounding in a study based on spatial, rather than temporal, contrasts.

A Method to Detect Residual Confounding in Spatial and Other Observational Studies