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oai:recercat.cat:10230/283292025-12-23T02:15:25Zcom_2072_6col_2072_452953

00925njm 22002777a 4500 dc Revilla, Melanie author Saris, Willem E. author 2017-03-30T08:24:19Z 2017-03-30T08:24:19Z 2011 Saris, Satorra and Coenders (2004) proposed a new approach to estimate the quality of survey questions, combining the advantages of two existing approaches: the multitrait-multimethod (MTMM) and the split-ballot (SB) ones. Implemented in practice, this new approach led to frequent problems of non-convergence and improper solutions. This paper uses Monte Carlo simulations to understand why the SB-MTMM is working well in some cases but not in others. The number of SB groups is a crucial element: the 3-group design is performing better. However, the 2-group design can also perform well: the analyses suggest that the interaction between the absolute values of the correlations between the traits and the relative values of the different correlations between traits play an important role. Split-ballot multitrait-multimethod approach Convergence Heywood cases Monte Carlo simulations Quality of survey questions The split-ballot multitrait-multimethod approach: Implementation and problems