An equal-level approach to the investigation of multitrait-multimethod matrices

Abstract

An equal-level approach that yields new information for the evaluation of multitrait-multimethod (MTMM) matrices is described. The procedure is based on the analysis of item-composite relations, composite-composite relations, composites, and facets. A main characteristic of the equal-level approach is the induction of equality in data-level prior to carrying out comparisons between coefficients, because in many cases such inequalities may lead to inaccurate conclusions. Methods are proposed for ensuring comparability of coefficients even if an MTMM design includes different numbers of items for traits and methods. The concept of disaggregation is assigned a key position in the investigation of convergent and discriminant validity. In addition, measures are proposed for avoiding other distortions resulting from partial self-correlations. Index terms: disaggregated correlations, equal-level approach, multitrait-multimethod analysis, partial self-correlations, Spearman-Brown formula.