Commentary: Correlated errors and energy adjustment--where are the data?

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Abstract
In this issue of the International Journal of Epidemiology (IJE), Day et al.1 conduct a sensitivity analysis of the effects of correlated errors of mis-measured covariates in linear regression models, when the data to permit direct adjustment for the effects of correlated errors are not available. They show yet again what has been documented many times before, but not cited by Day et al.,2 –6 that measurement error in more than one model covariate in which both the underlying true values and the errors may be correlated leads to a conflation of the well-known effects of confounding with the well-known effects of measurement error. When the correlations between the underlying variables, the error correlations, and the measurement errors are large, these results can be misleading and unpredictable. It is not entirely clear what is new here, although the detailed example is certainly useful to further emphasize this point to those who didn't get it the first few times around.

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