Empirical subtyping approaches rest on theories that emphasize the multifaceted nature of substance use and related behaviors (Basu et al., 2004; Moss et al., 2007). Due to the complexity of these phenomena, empirical subtyping approaches have outperformed traditional methods of subtyping (Ball et al., 1995; Epstein et al., 2002). Although a variety of univariate empirical subtyping approaches have been used (Craig et al., 1992; Ball et al., 1995), multivariate cluster analysis has been the method of choice to subtype substance dependence (Gelernter et al., 2005; Gelernter et al., 2006; Kranzler et al., 2008; Chan et al., 2011). This approach has been used successfully to identify subtypes of cocaine dependence (CD) (Kranzler et al., 2008) and opioid dependence (OD) (Chan et al., 2011). These subtypes allowed the identification of promising candidate regions in genome-wide linkage scans for CD (Gelernter et al., 2005) and OD (Gelernter et al., 2006). The approach used a range of cocaine or opioid use behaviors to which k-means (Seber, 1984), a classic non-hierarchical clustering method, was applied in combination with a hierarchical clustering method (Hastie et al.,
