Indicators for monitoring and improving representativeness of response

The increasing efforts and costs required to achieve survey response have led to a stronger focus on survey data collection monitoring by means of paradata and to the rise of adaptive and responsive survey designs. Indicators that support data collection monitoring, targeting and prioritising in such designs are not yet available. Subgroup response rates come closest but do not account for subgroup size, are univariate and are not available at the variable level. We present and investigate indicators that support data collection monitoring and effective decisions in adaptive and responsive survey designs. As they are natural extensions of R-indicators, they are termed partial R-indicators. We make a distinction between unconditional and conditional partial R-indicators. Unconditional partial R-indicators provide a univariate assessment of the impact of register data and paradata variables on representativeness of response. Conditional partial R-indicators offer a multivariate assessment. We propose methods for estimating partial indicators and investigate their sampling properties in a simulation study. The use of partial indicators for monitoring and targeting nonresponse is illustrated for both a household and a business survey. Guidelines for the use of the indicators are given.