Their critique’s rationale has two flaws. The first misconception has to do with latent class analysis. Latent class analysis can be considered a technique to unmix data or uncover taxonomies or nonarbitrary classes. Kendler et al. (2) (cited by Dr. Parker et al.), in an epidemiologically defined twin sample, performed a latent class analysis, identifying atypical depression as a distinct subgroup. Once latent classes are identified, Dillon and Goldstein (3) noted that "within a cluster, the items are independent" (uncorrelated). Dr. Parker and colleagues reported the expected low correlation of vegetative symptoms. Actually, when the entire group was examined, Dr. Parker et al. found three significant correlations (of a possible six): rejection with hypersomnia (p=0.02), weight gain with leaden paralysis (p=0.03), and another by inference (r=0.12, df=158, p<0.07). From the manner in which the data were presented on the third correlation, it is unclear which two symptoms had this correlation. Within the patient subset with reactive mood and one accessory symptom, there were no significant correlations. The anticipated occurred: a less homogeneous group exhibited significant correlations, and a cluster (homogeneous group) had uncorrelated symptoms. Angst et al. (4) reported a relevant analysis after the study by Dr. Parker and colleagues was accepted for publication. In a Zurich epidemiological sample, which, by definition, was heterogeneous, a high association between atypical depressive symptoms was found.