  Nonresponse bias is a widely prevalent problem for data collections. We
develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in
cross-sectional studies, and apply these steps to the Early Childhood
Longitudinal Study, Kindergarten Class of 2010-11. A key step is the
construction of indices of nonresponse bias based on proxy pattern-mixture
models for survey variables of interest. A novel feature is to characterize the
strength of evidence about nonresponse bias contained in these indices, based
on the strength of relationship of the characteristics in the nonresponse
adjustment with the key survey variables. Our NRBA incorporates missing at
random and missing not at random mechanisms, and all analyses can be done
straightforwardly with standard statistical software.
