Recent research finds that, for social desirability reasons, uninformed individuals disproportionately give “neither agree nor disagree” type responses to survey attitude questions, even when a “do not know” option is available. Such “face-saving” responses inflate the indifference (i.e., middle) categories of ordered attitude variables with nonordered responses. When such inflation occurs within the middle category of one's ordered dependent variable, estimates from ordered probit (and ordered logit) models are likely to be unreliable and inefficient. This article develops a set of mixture models that estimate and account for the presence of “face-saving” responses in middle categories of ordered survey response variables, and applies these models to (1) simulated data and (2) a commonly studied survey question measuring attitudes toward European Union (EU) membership among individuals in EU-candidate countries. Results from the survey data set and the Monte Carlo experiments suggest that, when middle category inflation is present in one's ordered dependent variable, the estimates obtained from middle category mixture models are less biased than—and in some cases substantively distinct from—the estimates obtained from “naive” ordered probit models.