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From average response rate to personalized protocol

Survey methods research first efforts to understand nonresponse started by looking at response rates. The focus was on finding methods that raided response rates. This approach might be useful when everyone has response propensities close to the average. The deterministic formulation of nonresponse bias may even reflect this sort of assumption. 

Researchers have since looked at subgroup response rates. Also interesting, but assuming that these rates are a fixed characteristic leaves us helpless. 

Now, it seems that we have begun working with an assumprton that there is heterogenous response to treatments and that we should, therefore, tailor the protocol and manipulate response propensities.  

I thought this development has a parallel in clinical trials where there is a new emphasis on personalized medicine. 

We still have important questions to resolve. For example, what are we trying to maximize?

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