Can biodata instruments developed to predict managerial success (e.g., rate of promotional progress) in one organization be similarly valid in other organizations, including organizations in different industries? The answer is yes, but this answer also needs to be qualified by the types of procedures used in developing the instrument. There are four factors believed to influence the generalizability of biodata instruments (Carlson, Scullen, Schmidt, Rothstein, & Erwin, 1999). First, the role of theory is crucial. Specifically, there should be clear reasons why the instrument would generalized to other populations and situations. In the absence of such clear expectations, some predictive relationships may not be observed in the new setting. Second, the criterion measure used for key development should be valid and reliable. When criterion measures are not adequate, there will be little accuracy in identifying meaningful relationships with the biodata items. Third, the validity of each item in the inventory should be determined. Doing so reduces the sample dependence of the instrument. Sample dependence increases when items are developed using an empirical as opposed to a theory-based approach (see Chapter 12). Finally, if large samples are used to develop the instrument, results are less likely to be affected as adversely by sampling error, and the chances of generalization increase.