Answer: Cross-informant data can be used to classify people as deviant vs. nondeviant by selecting a criterion appropriate for the user’s aims and the available data. For example, if the ASR and two ABCLs have been completed for each person, a user can elect to classify people as deviant on a particular syndrome if 2 of the 3 forms yield scores in the borderline or clinical range on that syndrome. Cross-informant data can also be combined quantitatively by converting raw scores to standard scores within a sample. Most statistical software has options for converting raw scores to standard scores with convenient parameters, such as mean = 100, SD = 15. The user can average the standard scores to obtain a composite cross-informant score for each person. The composite scores can then be analyzed statistically. Because the corresponding ASR and ABCL syndrome scales are assumed to measure a particular latent variable, structural equation modeling can also be used to analyze cross-informant data.