Estimating the Reliability of Single-Item Life Satisfaction Measures: Results from Four National Panel Studies
- 1.2k Downloads
Life satisfaction is often assessed using single-item measures. However, estimating the reliability of these measures can be difficult because internal consistency coefficients cannot be calculated. Existing approaches use longitudinal data to isolate occasion-specific variance from variance that is either completely stable or variance that changes systematically over time. In these approaches, reliable occasion-specific variance is typically treated as measurement error, which would negatively bias reliability estimates. In the current studies, panel data and multivariate latent state-trait models are used to isolate reliable occasion-specific variance from random error and to estimate reliability for scores from single-item life satisfaction measures. Across four nationally representative panel studies with a combined sample size of over 68,000, reliability estimates increased by an average of 16% when the multivariate model was used instead of the more standard univariate longitudinal model.
KeywordsReliability Life satisfaction STARTS model Measurement Longitudinal analyses Panel studies
The BHPS data were made available through the ESRC Data Archive. The data were originally collected by the ESRC Research Centre on Micro-social Change at the University of Essex (now incorporated within the Institute for Social and Economic Research). Neither the original collectors of the data nor the Archive bear any responsibility for the analyses or interpretations presented here. This paper also uses confidentialised unit record file from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA Project was initiated and is funded by the Commonwealth Department of Families, Community Services and Indigenous Affairs (FaCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (MIAESR). The findings and views reported in this paper, however, are those of the author and should not be attributed to either FaCSIA or the MIAESR. The GSOEP data were made available by the German Socio-Economic Panel Study at the German Institute for Economic Research (DIW), Berlin. Finally, the study uses data collected in the “Living in Switzerland” project, conducted by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS, University of Lausanne. The SHP project is financed by the Swiss National Science Foundation. This research was supported by National Institute on Aging grant R03AG032001.
- Alwin, D. F. (2007). Margins of error: A study of reliability in survey measurement. New York: Wiley.Google Scholar
- Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.Google Scholar
- Haisken-De New, J. P., & Frick, J. (2005). Desktop companion to the German Socio-Economic Panel Study (GSOEP). Berlin: DIW.Google Scholar
- Muthén, L. K., & Muthén, B. O. (1998–2009). Mplus user’s guide (5th Ed.). Los Angeles, CA: Muthén & Muthén.Google Scholar
- Taylor, M. F., Brice, J., Buck, N., & Prentice-Lane, E. (2004). British Household Panel Survey user manual volume A: Introduction, technical report, and appendices. Colchester: University of Essex. Available at: http://iserwww.essex.ac.uk/ulsc/bhps/doc/.
- Thompson, B. (Ed.). (2003). Score reliability: Contemporary thinking on reliability issues. Thousand Oaks, CA: Sage.Google Scholar
- University of Essex. Institute for Social and Economic Research. (2004). British Household Panel Survey; waves 1–12, 1991–2003 [computer file]. Colchester, Essex: UK Data Archive [distributor].Google Scholar
- Watson, N. (2010). HILDA user manual—release 8. Melbourne Institute of Applied Economic and Social Research, University of Melbourne.Google Scholar