2026-04-13T15:06:53Zhttps://recercat.cat/oai/requestoai:recercat.cat:10230/283292025-12-23T02:15:25Zcom_2072_6col_2072_452953
RECERCAT
author
Revilla, Melanie
author
Saris, Willem E.
2017-03-30T08:24:19Z2017-03-30T08:24:19Z2011
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.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properlyattributed. http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess
Split-ballot multitrait-multimethod approach
Convergence
Heywood cases
Monte Carlo simulations
Quality of survey questions
The split-ballot multitrait-multimethod approach: Implementation and problems
info:eu-repo/semantics/workingPaper