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Journal of Happiness Studies

, Volume 17, Issue 5, pp 1769–1787 | Cite as

Measurement Invariance of the Day Reconstruction Method: Results from the COURAGE in Europe Project

  • Blanca Mellor-Marsá
  • Marta Miret
  • Francisco J. Abad
  • Somnath Chatterji
  • Beatriz Olaya
  • Beata Tobiasz-Adamczyk
  • Seppo Koskinen
  • Matilde Leonardi
  • Josep Maria Haro
  • José Luis Ayuso-Mateos
  • Francisco Félix CaballeroEmail author
Research Paper

Abstract

Given the growing interest in the study of subjective well-being as a measure of social progress, instruments that produce valid and reliable scores and that can be used within and across countries are needed. The aim of the present study was to analyze the measurement equivalence of the Day Reconstruction Method in its brief version, using nationally representative samples from Finland, Poland, and Spain obtained within the COURAGE in Europe project. The goodness-of-fit of a two-correlated-factors model and the reliability of the scores obtained were assessed. Cross-country invariance was tested employing a multiple group confirmatory factor analysis, through sequential constraint imposition. In each country, measurement invariance was tested across time frames (morning, afternoon and evening) and days of the week (weekday and weekend). The results found support for the hypothesis of a two-correlated-factors (positive and negative affect) structure; the reliability of the positive, the negative and the net affect scores showed appropriate values. A high equivalence across the three national samples was found: all items except one showed strong measurement invariance indicating that respondents from Finland, Poland, and Spain attribute the same meaning to the latent construct under study, and the levels of the underlying items are equal in all three countries. Similar results were found for the measurement equivalence across time frames and days of the week. Our findings support the assumption of comparability across the different samples considered; in general, higher positive affect and lower negative affect were found in Finland, in the evening and at the weekend.

Keywords

Subjective well-being Day Reconstruction Method Multiple group confirmatory factor analysis Measurement invariance 

Notes

Acknowledgments

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under Grant Agreement Number 223071 (COURAGE in Europe), from the Instituto de Salud Carlos III-FIS research Grants Number PS09/00295 and PS09/01845, and from the Spanish Ministry of Science and Innovation ACI-Promociona (ACI2009-1010). The study was supported by the Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), and the AGES-CM Programme (AGES-S2010/BMD-2422). M.M. is grateful to the Spanish Ministry of Economy and Competitiveness for the postdoctoral fellowship (Reference No. FPDI-2013-15793). B.O. is grateful to the Sara Borrell postdoctoral programme (Reference No. CD12/00429) supported by the Instituto de Salud Carlos III, Spain.

Compliance with Ethical Standards

Disclosure of potential conflicts of interest

The authors declare that they have no conflict of interest. The views expressed in this paper are those of the authors, and do not necessarily represent the views or policies of the World Health Organization.

Research Involving Human Participants

Ethical approvals were obtained from all participant institutions. Informed consent from each individual was also obtained.

References

  1. Ayuso-Mateos, J. L., Miret, M., Caballero, F. F., Olaya, B., Haro, J. M., Kowal, P., et al. (2013). Multi-country evaluation of affective experience: validation of an abbreviated version of the day reconstruction method in seven countries. PLoS One, 8(4), e61534. doi: 10.1371/journal.pone.0061534.CrossRefGoogle Scholar
  2. Bradburn, N. M. (1969). The structure of psychological well-being. Chicago: Aldine.Google Scholar
  3. Bylsma, L. M., Taylor-Clift, A., & Rottenberg, J. (2011). Emotional reactivity to daily events in major and minor depression. Journal of Abnormal Psychology, 120(1), 155–167. doi: 10.1037/a0021662.CrossRefGoogle Scholar
  4. Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 3(105), 456–466.CrossRefGoogle Scholar
  5. Caballero, F. F., Miret, M., Olaya, B., Perales, J., López-Ridaura, R., Haro, J. M., et al. (2014). Evaluation of affect in Mexico and Spain: Psychometric properties and usefulness of an abbreviated version of the day reconstruction method. Journal of Happiness Studies, 15, 915–935.CrossRefGoogle Scholar
  6. Campo-Arias, A., & Oviedo, H. C. (2008). Propiedades Psicométricas de una Escala: la Consistencia Interna. Revista de Salud Pública, 10(5), 831–839.CrossRefGoogle Scholar
  7. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 2(9), 233–255.CrossRefGoogle Scholar
  8. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York: Academic Press.Google Scholar
  9. Deaton, A. (2008). Income, health, and well-being around the world: evidence from the Gallup World Poll. Journal of Economic Perspective, 22, 53–72.CrossRefGoogle Scholar
  10. Devins, G. M., Beiser, M., Dion, R., Pelletier, L. G., & Edwards, R. G. (1997). Cross-cultural measurement of psychological well-being: The psychometric equivalence of Cantonese, Vietnamese, and Laotian translations of the affect balance scale. American Journal of Public Health, 87, 794–799.CrossRefGoogle Scholar
  11. Diener, E., Ng, W., Harter, J., & Arora, R. (2010). Wealth and happiness across the world: Material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling. Journal of Personality and Social Psychology, 99, 52–61.CrossRefGoogle Scholar
  12. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276–302.CrossRefGoogle Scholar
  13. Dockray, S., Grant, N., Stone, A. A., Kahneman, D., Wardle, J., & Steptoe, A. (2010). A comparison of affect ratings obtained with ecological momentary assessment and the day reconstruction method. Social Indicators Research, 99(2), 269–283. doi: 10.1007/s11205-010-9578-7.CrossRefGoogle Scholar
  14. Dorans, N. J., & Schmitt, A. P. (1991). Constructed response and differential item functioning: A pragmatic approach. Princeton, NJ: Educational Testing Service.Google Scholar
  15. Drasgow, F., Levine, M. V., & McLaughlin, M. E. (1987). Detecting inappropriate test scores with optimal and practical appropriateness indices. Applied Psychological Measurement, 11, 59–79.CrossRefGoogle Scholar
  16. Elosua, P., & López-Jáuregui, A. (2002). Indicadores de dimensionalidad para ítems binarios. Metodología de las Ciencias del Comportamiento, 4, 121–137.Google Scholar
  17. Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups? Testing measurement invariance using the confirmatory factor analysis framework. [Research Support, N.I.H., Extramural Review]. Medical Care, 44(11 Suppl 3), S78–S94. doi: 10.1097/01.mlr.0000245454.12228.8f.CrossRefGoogle Scholar
  18. Hox, J. J., Mass, C. J. M., & Brinkhuis, J. S. (2010). The effect of estimation method and sample size in multilevel structural equation modeling. Statistica Neerlandica, 64, 157–170.CrossRefGoogle Scholar
  19. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRefGoogle Scholar
  20. Kahneman, D., Diener, E., & Schwarz, N. (1999). Well-being: The foundations of hedonic psychology. New York: Russell Sage Foundation.Google Scholar
  21. Kahneman, D., & Krueger, A. (2006). Developments in the measurement of subjective well-being. Journal of Economic Perspectives, 20, 3–24.CrossRefGoogle Scholar
  22. Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306(5702), 1776–1780. doi: 10.1126/science.1103572.CrossRefGoogle Scholar
  23. Kowal, P., Chatterji, S., Naidoo, N., Biritwum, R., Fan, W., Lopez Ridaura, R., et al. (2012). Data resource profile: The World Health Organization study on global ageing and adult health (SAGE). International Journal of Epidemiology, 41(6), 1639–1649. doi: 10.1093/ije/dys210.CrossRefGoogle Scholar
  24. Krueger, A. B., & Schkade, D. A. (2008). The reliability of subjective well-being measures. Journal of Public Economics, 92(8–9), 1833–1845. doi: 10.1016/j.jpubeco.2007.12.015.CrossRefGoogle Scholar
  25. Krueger, A. B., & Stone, A. A. (2008). Assessment of pain: A community-based diary survey in the USA. Lancet, 371(9623), 1519–1525. doi: 10.1016/S0140-6736(08)60656-X.CrossRefGoogle Scholar
  26. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.CrossRefGoogle Scholar
  27. Leonardi, M., Chatterji, S., Koskinen, S., Ayuso-Mateos, J. L., Haro, J. M., Frisoni, G., et al. (2013). Determinants of health and disability in ageing population: The COURAGE in Europe Project (Collaborative Research on Ageing in Europe). Clinical Psychology and Psychotherapy,. doi: 10.1002/cpp.1856.Google Scholar
  28. McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrance Erlbaum Associates.Google Scholar
  29. Miret, M., Caballero, F. F., Chatterji, S., Olaya, B., Tobiasz-Adamczyk, B., Koskinen, S., et al. (2014). Health and happiness: Results from the collaborative research on ageing in Europe (COURAGE in Europe) project. Bulletin of the World Health Organization, 92(10), 716–725.CrossRefGoogle Scholar
  30. Miret, M., Caballero, F. F., Mathur, A., Naidoo, N., Kowal, P., Ayuso-Mateos, J. L., et al. (2012). Validation of a measure of subjective well-being: An abbreviated version of the day reconstruction method. PLoS One,. doi: 10.1371/journal.pone.0043887.Google Scholar
  31. Mulaik, S. A. (1972). The foundations of factor analysis. New York: McGraw Hill.Google Scholar
  32. Muthén, L. K., & Muthén, B. O. (2010). Mplus user’s guide (4th ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
  33. Napier, A. D., Ancarno, C., & Butler, B. (2014). Culture and health. Lancet, 384, 1607–1639.CrossRefGoogle Scholar
  34. Oishi, S. (2010). Culture and well-being: Conceptual and methodological issues. In J. F. H. E. Diener & D. Kahneman (Eds.), International differences in wellbeing (pp. 34–69). New York: Oxford University Press.CrossRefGoogle Scholar
  35. Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114, 552–566.CrossRefGoogle Scholar
  36. Russell, J. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145–172.CrossRefGoogle Scholar
  37. Ryan, R. M., Bernstein, J. H., & Brown, K. W. (2010). Weekends, work, and well-being: Psychological need satisfactions and day of the week effects on mood, vitality, and physical symptoms. Journal of Social and Clinical Psychology, 29(1), 95–122.CrossRefGoogle Scholar
  38. Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99(6), 323–338.CrossRefGoogle Scholar
  39. Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  40. StataCorp. (2010). Stata statistical software. Release 11. College Station, TX: Stata Corporation.Google Scholar
  41. Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modelling. Personality and Individual Differences, 42, 893–898.CrossRefGoogle Scholar
  42. The World Bank (2011). http://data.worldbank.org/country.
  43. Üstün, T. B., Chatterji, S., Mechbal, A., Murray, C. J. L., & WHS Collaborating groups (2005). Quality assurance in surveys: Standards, guidelines and procedures. In Department of Economic and Social Affairs Statistic Division of the United Nations (Ed.), Household surveys in developing and transition countries. New York: United Nations Statistics Division.Google Scholar
  44. van de Schoot, R. L., Lugtig, P., & Hox, J. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology. European Journal of Developmental Psychology, 9, 486–492.CrossRefGoogle Scholar
  45. Vázquez, C., & Hervás, G. (2013). Addressing current challenges in cross-cultural measurement of well-being: The pemberton happiness index. In A. D. Fave & H. H. Koop (Eds.), Well-being and cultures. Perspectives from positive psychology (pp. 31–49). New York: Springer.Google Scholar
  46. Wainer, H., & Thissen, D. (2001). True score theory: The traditional method. In D. Thissen & H. Wainer (Eds.), Test Scoring. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  47. Watkins, L. (2010). The cross-cultural appropriateness of survey-based value(s) research: A review of methodological issues and suggestion of alternative methodology. International Marketing Review, 27(6), 694–716.Google Scholar
  48. Wilkinson, R. G., & Pickett, K. E. (2007). The problems of relative deprivation: Why some societies do better than others. Social Science and Medicine, 65, 1965–1978.CrossRefGoogle Scholar
  49. Wilkinson, R. G., & Pickett, K. E. (2009). The spirit level: Why more equal societies almost always do better. London: Penguin Books.Google Scholar
  50. Zieky, M. (1993). Practical questions in the use of DIF statistics in test development. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 337–347). New Jersey: Lawrence Erlbaum Associates.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Blanca Mellor-Marsá
    • 1
    • 2
    • 3
  • Marta Miret
    • 1
    • 2
    • 3
  • Francisco J. Abad
    • 4
  • Somnath Chatterji
    • 5
  • Beatriz Olaya
    • 2
    • 6
  • Beata Tobiasz-Adamczyk
    • 7
  • Seppo Koskinen
    • 8
  • Matilde Leonardi
    • 9
  • Josep Maria Haro
    • 2
    • 6
  • José Luis Ayuso-Mateos
    • 1
    • 2
    • 3
  • Francisco Félix Caballero
    • 1
    • 2
    • 3
    Email author
  1. 1.Department of PsychiatryUniversidad Autónoma de MadridMadridSpain
  2. 2.Instituto de Salud Carlos IIICentro de Investigación Biomédica en Red de Salud Mental. CIBERSAMMadridSpain
  3. 3.Instituto de Investigación Sanitaria Princesa (IIS-IP)Hospital Universitario de la PrincesaMadridSpain
  4. 4.Department of Social Psychology and MethodologyUniversidad Autónoma de MadridMadridSpain
  5. 5.Department of Health Statistics and Information SystemsWorld Health OrganizationGenevaSwitzerland
  6. 6.Parc Sanitari Sant Joan de DéuUniversitat de BarcelonaBarcelonaSpain
  7. 7.Department of Medical SociologyJagiellonian University Medical CollegeKrakowPoland
  8. 8.National Institute for Health and WelfareHelsinkiFinland
  9. 9.Fondazione IRCCSNeurological Institute Carlo BestaMilanItaly

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