The Split-Ballot Multitrait-Multimethod Approach: Implementation and Problems

Structural Equation Modeling

Volumn 20, Issue 1, 2013, Pages 27-46

  Revilla, Melanie ^a   Saris, Willem E ^a  

^a UNIVERSITAT POMPEU FABRA   (Spain)

Author keywords

convergence; Heywood cases; Monte Carlo simulations; quality of survey questions; split ballot multitrait multimethod approach

Indexed keywords

ABSOLUTE VALUES; CONVERGENCE; HEYWOOD CASES; IMPROPER SOLUTION; MONTE CARLO SIMULATIONS; NEW APPROACHES; RELATIVE VALUE; SPLIT-BALLOT MULTITRAIT-MULTIMETHOD APPROACH;

SURVEYS;

MONTE CARLO METHODS;

EID: 84873354206     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1080/10705511.2013.742379     Document Type: Article

References (27)

1. Alwin, D. F. 1997. Feeling thermometers versus 7-point scales: Which are better?. Sociological Methods and Research, 25: 318
2. Alwin, D. F. 2007. Margins of errors: A study of reliability in survey measurement New York, NY: Wiley-Interscience.
3. Andrews, F. 1984. Construct validity and error components of survey measures: A structural modeling approach. Public Opinion Quarterly, 46: 409-442.
4. Browne, M. W. 1984. The decomposition of multitrait-multimethod matrices. British Journal of Mathematical and Statistical Psychology, 37: 1-21.
5. Campbell, D. T. and Fiske, D. W. 1959. Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 6: 81-105.
6. Corten, I. W., Saris, W. E., Coenders, G. M., van der Veld, W., Aalberts, C. E. and Kornelis, C. 2002. Fit of different models for multitrait-multimethod experiments. Structural Equation Modeling, 9: 213-232.
7. Cudeck, R. 1988. Multiplicative models and MTMM matrices. Journal of Educational Statistics, 13: 131-147.
8. Eid, M. 2000. A multitrait-multimethod model with minimal assumptions. Psychometrika, 65: 241-261.
9. Jöreskog, K. G. 1970. A general method for the analysis of covariance structures. Biometrika, 57: 239-251.
10. Jöreskog, K. G. 1971. Statistical analysis of sets of congeneric tests. Psychometrika, 36: 109-133.
11. Jöreskog, K. G. and Sörbom, D. 1991. LISREL VII: A guide to the program and applications Chicago, IL: SPSS.
12. Kolenikov, S. and Bollen, K. A. 2008. Testing negative error variances: Is a Heywood case a symptom of misspecification?, University of North Carolina, Chapel Hill. http://web.missouri.edu/~kolenikovs/papers/heywood-8.pdfUnpublished paper available at:
13. Költringer, R. 1993. Messqualität in der sozialwissenschaftlichen Umfrageforschung. Endbericht Project P8690-SOZ des Fonds zur Förderung der wissenschaftlichen Forschung (FWF) [Measuring quality in social science survey research final project P8690-515SCO the fund for scientific research (FWF)] Wien, Germany
14. Muthén, L. K. and Muthén, B. O. 1998-2007. Mplus user's guide, 5th ed. Los Angeles, CA: Muthén & Muthén.
15. Revilla, M., Saris, W. E. and Krosnick, J. A. 2012. "Choosing the number of categories in agree-disagree scales.". In Accepted in Sociological Methods and Research
16. Rindskopf, D. 1984. Structural equation models. Sociological Methods & Research, 13: 109
17. Saris, W. E. and Aalberts, C. 2003. Different explanations for correlated disturbance terms in MTMM studies. Structural Equation Modeling, 10: 193-213.
18. Saris, W. E. and Andrews, F. M. 1991. "Evaluation of measurement instruments using a structural modeling approach.". In Measurement errors in surveys Edited by: Biemer, P. P., Groves, R. M., Lyberg, L., Mathiowetz, N. and Sudman, S. 575-597. New York, NY: Wiley.
19. Saris, W. E. and Gallhofer, I. 2007. Design, evaluation, and analysis of questionnaires for survey research New York, NY: Wiley.
20. Saris, W. E., Satorra, A. and Coenders, G. 2004. A new approach to evaluating the quality of measurement instruments: The split-ballot MTMM design. Sociological Methodology, 34: 311-347.
21. Saris, W. E., Satorra, A. and Van der Veld, W. M. 2009. Testing structural equation models or detection of misspecifications?. Structural Equation Modeling, 16: 561-582.
22. Scherpenzeel, A. C. 1995. A question of quality: Evaluating survey questions by multitrait-multimethod studies Amsterdam, Netherlands: Nimmo.
23. Van der Veld, W. M., Saris, W. E. and Satorra, A. 2008. Judgment Aid Rule [Software]. JRule 2.0 User Manual (unpublished manuscript, internal report) The Netherlands: Radbound University Nijmegen.
24. Van Driel, O. P. 1978. On various causes of improper solutions in maximum likelihood factor analysis. Psychometrika, 43: 225-243.
25. Van Meurs, L. and Saris, W. E. 1990. "Memory effects in MTMM studies.". In Evaluation of measurement instruments by meta-analysis of multitrait-multimethod studies Edited by: Saris, W. E. and van Meurs, L. Amsterdam, Netherlands: North Holland.
26. Werts, C. E. and Linn, R. L. 1970. Path analysis: Psychological examples. Psychological Bulletin, 74: 194-212.
27. Wothke, W. 1996. "Models for multitrait-multimethod matrix analysis.". In Advanced structural equation modeling: Issues and techniques Edited by: Marcoulides, G. A. and Schumacker, R. E. 7-56. Mahwah, NJ: Lawrence Erlbaum.