Quantitative research on sexual minority youths (SMYs) has likely contributed to misperceptions about the risk and deviance of this population. In part because it often relies on self-reported data from population-based self-administered questionnaires, this research is susceptible to misclassification bias whereby youths who are not SMYs are classified as such and vice versa. I introduce a taxonomy of classification errors, including seven unique sources, and discuss the potential effects of each error on estimates of youth outcomes. Through examples, I illustrate how researchers can detect and correct such errors and discuss how piecewise attempts to address bias can sometimes unintentionally exacerbate other forms of bias. Finally, I propose a unified conceptual model for addressing the various error sources, urging researchers to take a proactive and integrative approach to data validity by attending to errors at each step in the research process, from questionnaire development to data analysis. Although I focus on errors specific to the topic of sexuality research on youths, this argument can serve as a broader template for the development of taxonomies of error along other dimensions considered in educational research, such as race and disability status.