Structural Equation Modeling: Applications Using Mplus

2.2 CFA Model with Continuous Indicators

Having introduced the basic concepts of CFA models, let us turn our attention to application of CFA with continuous indicators in the framework of the Mplus program. In this section, we demonstrate how to run the example CFA model proposed in Section 2.1 using real data. Data used here are from a natural history study of rural illicit drug users in Ohio, USA. Such a population is an important population for testing BSI- 18, given the high rates of psychiartric distress both as a consequence of their drug use and as a pre- existing condition for which they are self- medicating (Grant et al., 2004). A total sample of 248 drug users was recruited from three rural counties in Ohio: respondent- driven sampling (RDS) was used for sample recruitment (Heckathorn, 1997, 2002; Wang et al., 2007). A detailed description on recruitment approaches and sample characteristics can be found in the literature (Siegal et al., 2006).

Recall that the responses to the BSI- 18 items are measured on a five- point Likert scale: 0, not at all; 1, a little bit; 2, moderately; 3, quite a bit; and 4, extremely. Although they are actually ordinal scales, Likert scales are often treated as numeric measures in CFA, as well as in other statistical modeling. We will treat the observed indicators as numeric and ordinal measures, respectively, and recode them as binary measures for the purpose of model demonstrations. The following Mplus program or syntax file estimates a ...