ABSTRACT
This chapter explores a phenomenon that occurs to some degree in the process of fitting virtually any statistical model to empirical data. The phenomenon involves a kind of uncertainty that is inherent in parameter estimates, uncertainty arising from the sensitivity of the relationship between those parameter estimates and the fit of the model to the data. If there is low sensitivity in this relationship, then small changes in model fit would be associated with large changes in parameter estimates. Under such circumstances, very different parameter estimates will be associated with nearly identical model fit, calling into question an investigator's substantive interpretation of the optimal parameter estimates. On the other hand, high sensitivity would mean that small changes in fit would be associated with small changes in parameter estimates, thus supporting more rigorous substantive interpretation of parameter estimates.
