Latent profile analysis (LPA) is derived from conventional latent class analysis, originally introduced by Lazarsfeld and Henry (1968) for the purposes of deriving latent attitude variables from responses to dichotomous survey items. Important contributions to latent class analysis have been made by Clogg (1995). For a review, see Magidson and Vermunt (2004) and Kaplan, Kim, and Kim (2009). In a traditional latent class analysis, it is assumed that an individual belongs to one and only one latent class, and that – given an individual’s latent class membership – the observed responses are independent of one another (referred to as the assumption of local independence). The latent classes arise from the patterns of response frequencies to categorical items, where the response frequencies play a role similar to that of the correlation matrix in factor analysis (Lanza, Collins, Lemmon and Schafer, 2007). The analogue of factor loadings are parameters that estimate the probability of a particular response on the manifest indicators given membership in the latent class. Unlike continuous latent variables (i.e. factors), categorical latent variables (latent classes) divide individuals into mutually exclusive and exhaustive groups.