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A Method to Analyse Measurement Invariance under Uncertainty in Between-Subjects Design

Published online by Cambridge University Press:  10 January 2013

José A. Martínez*
Affiliation:
Universidad Politécnica de Cartagena (Spain)
Manuel Ruiz Marin
Affiliation:
Universidad Politécnica de Cartagena (Spain)
Maria del Carmen Vivo Molina
Affiliation:
Fundación para la Formación e Investigación Sanitaria de la Región de Murcia (Spain)
*
Correspondence concerning this article should be addressed to José Antonio Martínez García. Departamento de Economía de la Empresa, Facultad de Ciencias de la Empresa, Universidad Politécnica de Cartagena. Paseo Alfonso XIII, 30203 Cartagena – Murcia (Spain). Phone: +34-968325776. E-mail: [email protected]

Abstract

In this research we have introduced a new test (H-test) for analyzing scale invariance in between group designs, and considering uncertainty in individual responses, in order to study the adequacy of disparate rating and visual scales for measuring abstract concepts. The H-test is easy to compute and, as a nonparametric test, does not require any a priori distribution of the data nor conditions on the variances of the distributions to be tested. We apply this test to measure perceived service quality of consumers of a sports services. Results show that, without considering uncertainty, the 1-7 scale is invariant, in line with the related works regarding this topic. However, de 1-5 scale and the 1-7 scale are invariant when adding uncertainty to the analysis. Therefore, adding uncertainty importantly change the conclusions regarding invariance analysis. Both types of visual scales are not invariant in the uncertainty scenario. Implications for the use of rating scales are discussed.

En esta investigación presentamos un nuevo test (test H) para analizar la invarianza de escala en diseños entre sujetos, considerando además la incertidumbre en las respuestas de los individuos, con el fin de estudiar la idoneidad de diferentes escalas de medición de conceptos abstractos. El test H es fácil de calcular y, debido a su naturaleza no paramétrica, no requiere ninguna asunción a prior sobre la distribución de los datos ni de las condiciones de la varianza. Aplicamos este test para medir la calidad percibida de los consumidores de servicios deportivos, y los resultados muestran que, sin considerar la incertidumbre, la escala de 1 a 7 es invariante, en línea con las conclusiones obtenidas en otras investigaciones. Sin embargo, al añadir la incertidumbre en el análisis, las escalas de 1 a 5 y de 1 a 7 son invariantes. Por tanto, la consideración de la incertidumbre cambia las conclusiones en relación al análisis de la invarianza de escala. Las escalas visuales consideradas, a su vez, no son invariantes. Finalmente, las implicaciones para el uso de escalas de medición son discutidas.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2012

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References

Amigo, S., Caselles, A., & Micó, J C. (2010). General factor of personality questionnaire (GFPQ): Only one factor to understand personality? The Spanish Journal of Psychology, 13, 517.CrossRefGoogle ScholarPubMed
Cohen, P., Cohen, J., Aiken, L., & West, S. (1999). The problem of units and the circumstance for POMP. Multivariate Behavioral Research, 34, 315346. http://dx.doi.org/10.1207/S15327906MBR3403_2CrossRefGoogle Scholar
Cox, E. P. (1980). The optimal number of response alternatives for a scale: A review. Journal of Marketing Research, 17, 407422.CrossRefGoogle Scholar
Cresswell, S. L., & Eklund, R. C. (2006). The convergent and discriminant validity of burnout measures in sport: A multitrait/multi-method analysis. Journal of Sports Sciences, 24, 209220. http://dx.doi.org/10.1080/02640410500131431CrossRefGoogle Scholar
Gardner, D. G., Cummings, L. L., Dunham, R. B., & Pierce, Jon L. (1998). Single-item versus multiple item measurement: An empirical comparison. Educational and Psychological Measurement, 58, 898915. http://dx.doi.org/10.1177/0013164498058006003CrossRefGoogle Scholar
Gregg, M., & Hall, C. (2006). Measurement of motivational imagery abilities in sport. Journal of Sport Sciences, 24, 961971. http://dx.doi.org/10.1080/02640410500386167CrossRefGoogle ScholarPubMed
Hayduk, L. A. (1996). LISREL Issues, debates and strategies. Baltimore, MD: The Johns Hopkins University Press.CrossRefGoogle Scholar
Hersh, H. M., & Caramazza, A. (1976). A fuzzy set approach to modifiers and vagueness in natural language. Journal of Experimental Psychology, 105, 254276. http://dx.doi.org/10.1037//0096-3445.105.3.254CrossRefGoogle Scholar
Kilpatrick, F. P., & Cantril, H. (1960). Self-anchoring scaling: A measure of individuals' unique reality worlds. Journal of Individual Psychology, 16, 158173.Google Scholar
Ko, Y. J., & Pastore, D. L. (2005). A hierarchical model of service quality for the recreational sport industry. Sport Marketing Quarterly, 14(2), 8497.Google Scholar
Martindale, R. J. J., Collins, D., Wang, J. C. K., McNeill, M., Lee, K. S., Sproule, J., & Westbury, T. (2010). Development of the talent development environment questionnaire for sport. Journal of Sports Sciences, 28, 12091221. http://dx.doi.org/10.1080/02640414.2010.495993CrossRefGoogle ScholarPubMed
Martínez, J. A., Ko., Y. J., & Martínez, L. (2010). An application of fuzzy logic to service quality research: A case of fitness service. Journal of Sport Management, 24, 502523.CrossRefGoogle Scholar
Martínez, J. A., & Ruiz, M. (2011). D-test: A new test for analyzing scale invariance using symbolic dynamics and symbolic entropy. Methodology. 7, 8895. http://dx.doi.org/10.1027/1614-2241/a000026CrossRefGoogle Scholar
Nicolai, A. T., & Dautwiz, J. M. (2010). Fuzziness in action: What consequence has the linguistic ambiguity of the core competence concept for organizational usage? British Journal of Management, 21, 874888. http://dx.doi.org/10.1111/j.1467-8551.2009.00662.xCrossRefGoogle Scholar
San Martín, J., Perles, F., & Canto, J. (2010). Life satisfaction and perception of happiness among university students. The Spanish Journal of Psychology, 13, 617628.CrossRefGoogle ScholarPubMed
Scherpenzeel, A. C., & Saris, W. E. (1997). The validity and reliability of survey questions: A meta-analysis of MTMM studies. Sociological Methods and Research, 25, 341383. http://dx.doi.org/10.1177/0049124197025003004CrossRefGoogle Scholar
Schmidt, F. L., & Hunter, J. E. (1996). Measurement error in psychological research: Lessons from 26 research scenarios. Psychological Methods, 1, 199223. http://dx.doi.org/10.1037//1082-989X.1.2.199CrossRefGoogle Scholar
Schmidt, F. L., & Hunter, J. E. (1999). Theory testing and measurement error. Intelligence, 27(3), 183198. http://dx.doi.org/10.1016/S0160-2896(99)00024-0CrossRefGoogle Scholar
Shamir, B., & Kark, R. (2004). A single-item graphic scale for the measurement of organizational identification. Journal of Occupational and Organizational Psychology, 77, 115123. http://dx.doi.org/10.1348/096317904322915946CrossRefGoogle Scholar
Spanos, A. (2010). The discovery of Argon: A case for learning from data? Philosophy of Science, 77, 359380. http://dx.doi.org/10.1086/652961CrossRefGoogle Scholar
Zaltman, G., & Zaltman., L. (2008). Marketing metaphoria: What deep metaphors teveal about the minds of consumers. Boston, MA: Harvard Business School Press.Google Scholar