Abstract:

Diener’s recommendation that researchers assess well-being by combining scores on Satisfaction with Life (SWLS), positive affect (PA), and negative affect (NA) has been nearly universally adopted. Latent variables that represent subjective well-being (SWB) in structural equation models often include SWLS, PA and NA as multiple indicators. However, Diener and his colleagues have also pointed out that PA and NA have different predictors. In order to compare structural models in which NA is combined with other indicators of well-being with models in which NA is treated as a separate outcome, we collected data on SWB, neuroticism, extraversion, and global social support for college students (N = 847). Structural Equation Model 1, in which NA was one of several indicators of SWB, was compared with three other models that represented NA as a separate outcome. Better model fit was obtained when NA was represented as a separate outcome variable, rather than as one of several indicators of SWB. This type of model also yields more information about the different predictors for positive and negative components of well-being. In future research, data analysts may consider representing NA and other negative emotional outcomes as separate dependent variables, instead of treating them as (reverse scored) indicators of SWB.

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