Individuals routinely rate themselves higher than their peers on a number of attributes and capabilities, including their satisfaction with life. However, the construct validity of this above-average effect requires specific psychometric properties of ratings of one's contentment and ratings of others' perceived contentment. This article tests these properties with respect to the popular Satisfaction With Life Scale through a multivariate measurement model with latent change and method effects. The model is fitted to two independent data sets (N = 597 and N = 964), and it is found twice that four items are suitable to compute a meaningful composite difference score. It is concluded that the above-average effect is a systematic multivariate phenomenon that can be assessed by the difference of two manifest, absolute evaluation scores.
Bonnefon, J.F., & Villejoubert, G. (2006). Tactful or doubtful? Expectations of politeness explain the severity bias in the interpretation of probability phrases. Psychological Science, 17, 747-751.
2.
Borsboom, D., Mellenbergh, G.J., & van Heerden, J. (2003). The theoretical status of latent variables. Psychological Review, 110, 203-219.
3.
Byrne, B.M., Shavelson, R.J., & Muthén, B.O. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456-466.
4.
Chambers, J.R., & Windschitl, P.D. (2004). Biases in social comparative judgments: The role of non-motivated factors in above-average and comparative-optimism effects. Psychological Bulletin, 130, 813-838.
5.
Diener, E., Emmons, R.A., Larsen, R.J., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49, 71-76.
6.
Eid, M. (2000). A multitrait-multimethod model with minimal assumptions . Psychometrika, 65, 241-261.
7.
Eid, M., Lischetzke, T., Nussbeck, F.W., & Trierweiler, L. (2003). Separating trait effects from trait-specific method effects in multitrait-multimethod models: A multiple-indicator CT-C(M-1) model. Psychological Methods, 8, 38-60.
8.
Fischer, G.H. (1987). Applying the principles of specific objectivity and of generalizability to the measurement of change. Psychometrika , 52, 565-587.
9.
Fischer, G.H., & Ponocny, I. (1994). An extension of the partial credit model with an application of the measurement of change. Psychometrika , 59, 177-192.
10.
Klar, Y., & Giladi, E. (1999). Are most people happier than their peers, or are they just happy? Personality and Social Psychology Bulletin , 25, 586-595.
11.
Lykken, D., & Tellegen, A. (1996). Happiness is a stochastic phenomenon. Psychological Science, 7, 186-189.
12.
McDonald, R.P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum.
13.
Muthén, B.O., & Asparouhov, T. (2002). Latent variable analysis with categorical outcomes: Multiple-group and growth modeling in Mplus (Mplus Web Notes No. 4). Los Angeles : Muthén & Muthén.
Raykov, T. (1999). Are simple change scores obsolete? An approach to studying correlates and predictors of change. Applied Psychological Measurement, 23, 120-126.
16.
Raykov, T. (2001). On the use and utility of the reliability coefficient in social and behavioral sciences. Quality and Quantity, 35, 253-263.
17.
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.
18.
Steyer, R. (1988). Conditional expectations: An introduction to the concept and its applications in empirical sciences. Methodika , 2, 53-78.
19.
Steyer, R. (1989). Models of classical psychometric test theory as stochastic measurement models: Representation, uniqueness, meaningful-ness, identifiability, and testability. Methodika, 3, 25-60.
20.
Steyer, R., Eid, M., & Schwenkmezger, P. (1997). Modeling true intraindividual change: True change as a latent variable. Methods of Psychological Research Online, 2, 21-33.
21.
Takane, Y., & de Leeuw, J. (1987). On the relationship between item response theory and factor analysis of discretized variables. Psychometrika , 52, 393-408.
22.
Vautier, S., Mullet, E., & Jmel, S. (2004). Assessing the structural robustness of self-rated satisfaction with life: A SEM analysis. Social Indicators Research, 86, 225-238.
23.
Zimmerman, D.W., & Williams, R.H. (1998). Reliability of gain scores under realistic assumptions about properties of pre-test and post-test scores . British Journal of Mathematical and Statistical Psychology , 51, 343-351.
24.
Zumbo, B.D., & Rupp, A.A. (2004). Responsible modeling of measurement data for appropriate inferences: Important advances in reliability and validity theory. In D. Kaplan (Ed.), The SAGE handbook of quantitative methodology for the social sciences (pp. 73-92). Thousand Oaks, CA: Sage.
