Nonrandom missing data can distort estimates of substantive relationships. In elaborating this principle for organizational research, we first develop a theoretical expectation that missing data in organizational surveys will normally be nonrandom relative to important organizational characteristics. We summarize empirical findings from a previous paper that demonstrate that unit nonresponse is a predictable outcome of organizational processes. Next, we examine expectations about organizational processes and item nonresponse and find that nonresponse is systematically associated with variables that tap organizational authority, capacity and motive to respond. In light of these findings, we develop suggestions for future organizational survey design to minimize missing data problems. We also outline approaches for analyses of organizational data in the presence of selection biases associated with unit and item nonresponse.

* North Carolina State University