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We outline a framework for multiple imputation of nonignorable itemnonresponse when the marginal distributions of some of the variables withmissing values are known. In particular, our framework ensures that (i) thecompleted datasets result in design-based estimates of totals that areplausible, given the margins, and (ii) the completed datasets maintainassociations across variables as posited in the imputation models. To do so, wepropose an additive nonignorable model for nonresponse, coupled with arejection sampling step. The rejection sampling step favors completed datasetsthat result in design-based estimates that are plausible given the knownmargins. We illustrate the framework using simulations with stratifiedsampling.

Multiple Imputation for Nonignorable Item Nonresponse in Complex Surveys Using Auxiliary Margin