  Often, government agencies and survey organizations know the population
counts or percentages for some of the variables in a survey. These may be
available from auxiliary sources, for example, administrative databases or
other high quality surveys. We present and illustrate a model-based framework
for leveraging such auxiliary marginal information when handling unit and item
nonresponse. We show how one can use the margins to specify different
missingness mechanisms for each type of nonresponse. We use the framework to
impute missing values in voter turnout in a subset of data from the U.S.\
Current Population Survey (CPS). In doing so, we examine the sensitivity of
results to different assumptions about the unit and item nonresponse.
