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Covariates of Measurement Error

I've been working on some mixed-mode problems where nonresponse and measurement error are confounded. I recently read an interesting article on using adjustment models to disentangle the two sources of error. The article is by Vannieuwenhuyze, Loosveldt, and Molenberghs. They suggest that you can make adjustments for measurement error if you have things that predict when those errors occur. They give specific examples. It's things that measure social conformity and other hypothesized mechanisms that lead to response error.

This was very interesting to read about. I suppose that just as with nonresponse, the predictors of this error -- in order to be useful -- need to predict when those errors occur and the survey outcome variables themselves. This is a new and difficult task... but one worth solving giving the push to use mixed mode designs.

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