In this chapter we first described how CFA can be used to model multitrait by multisource matrices to determine the convergent and discriminant validity of measures in clinical psychology. Here we described the outcomes necessary for measures to have strong construct validity as well as the less-than-ideal outcomes for the construct validity of measures. We hope that our description of how to use CFA to model multitrait by multisource matrices results in more researchers using these procedures as part of the evaluation of clinical psychology measures.
We then reviewed the studies in clinical psychology that used CFA to model multitrait by multi-source matrices. First, these procedures have seldom been used in clinical psychology. And, when these procedures are used, the studies indicate that most of the clinical psychology measures contain more source than trait variance, therefore suggesting poor construct validity for the measures. These results (Table 27.1) provide additional data for why clinical decisions should not be made on the basis of a single source. In our opinion, the field of clinical psychology should make greater use of these procedures for measurement development as well as to understand the nature of the strong source effects.
Our final suggestion concerned the need to expand the Campbell and Fiske (1959) multitrait by multimethod matrix in terms of multiple types of information (e.g., facets, modes, dimensions, instruments, methods, sources, occasions, and settings). We suggested that this expanded measurement matrix provides a richer framework for the development and the evaluation of measures. The careful use of this matrix should provide a more detailed understanding of the multiple causes of variability in clinical psychology measures and thus a better understanding of clinical phenomena.
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