Widaman, Keith F.2011-03-292011-03-291985Widaman, Keith F. (1985). Hierarchically nested covariance structure models for multitrait-multimethod data. Applied Psychological Measurement, 9, 1-26. doi:10.1177/014662168500900101doi:10.1177/014662168500900101https://hdl.handle.net/11299/102018A taxonomy of covariance structure models for representing multitrait-multimethod data is presented. Using this taxonomy, it is possible to formulate alternate series of hierarchically ordered, or nested, models for such data. By specifying hierarchically nested models, significance tests of differences between competing models are available. Within the proposed framework, specific model comparisons may be formulated to test the significance of the convergent and the discriminant validity shown by a set of measures as well as the extent of method variance. Application of the proposed framework to three multitrait-multimethod matrices allowed resolution of contradictory conclusions drawn in previously published work, demonstrating the utility of the present approach.enArticle