  Nonresponse bias is a widely prevalent problem for data on education. 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 the relationship between the characteristics in the
nonresponse adjustment and the key survey variables. Our NRBA improves existing
methods by incorporating both missing at random and missing not at random
mechanisms, and all analyses can be done straightforwardly with standard
statistical software.
