Confirmatory factor analysis (CFA), latent class analysis (LCA), and factor mixture models (FMM) were applied to the 11 DSM-IV opioid abuse and dependence criteria (Table 3). The models were also run without the legal criterion, since it is likely to be excluded from substance use disorders in DSM-V, in order to determine if this would make a difference to the latent structure of the diagnosis. Although the DSM-IV separates abuse from dependence, abuse and dependence criteria were included because many studies have found that in general population and other samples, substance abuse and dependence criteria form a unidimensional structure [15-17, 19, 21]. The abuse criteria were also included to provide more information and an improved ability to grade people on a continuum of severity. In the early stages of model development, exploratory factor analysis (EFA) is typically used instead of CFA to determine the number of factors that best fit the data. However, many studies over the past 20 years have confirmed that the substance abuse and dependence criteria form either one or two factors [14-23]. In the current analysis, one and two factor models were tested.
