MULTITRAIT-MULTIMETHOD INFORMATION MANAGEMENT: GLOBAL STRATEGIC ANALYSIS ISSUES

International researchers commonly encounter fitting problems when analyzing Multitrait-Multimethod data with confirmatory factor analysis (CFA) in both domestic and cross-cultural research (Scherpenzeel and Saris 1997). In 1992, Kenny and Kashy examined a special case of one of the most frequently used CFA models using one data set and found that it was not statistically identified and, therefore, not estimable. They then argued that most MTMM data were likely to conform closely to this special case, and because of this, alternative CFA models should be utilized in most data analysis. In this study nine data sets are analyzed using five different additive factor analytic models (CFA with inequality constraints, CFA with error variances fixed to uniqueness estimates from exploratory factor analysis, Rindskopf parameterization, correlated errors model, and a combination of the Rindskopf correlated errors model) and one multiplicative factor analytic (MUTMUM) model. As with previous attempts, myriad fitting problems were encountered with all six alternative specifications. Closer inspection indicates fitting problems may be due to imperfections in the data rather than fundamental flaws with the model specifications- indicating possible problems with the robustness of the techniques utilized. Several suggestions for improving international research to possibly avoid these problems are provided as are alternative methods of estimating construct validity.