Bad news indeed for Ryff’s six-factor model of well-being

Springer and Hauser (An Assessment of the Construct Validity of Ryff’s Scales of Psychological Well-Being: Method, Mode, and Measurement Effects. 2006. Social Science Research 35) tested one key aspect of the validity of Ryff’s six-factor model of psychological well-being (RPWB), namely, whether there is substantial independent variation among the six factors. In several large and heterogeneous samples, under a variety of model specifications, and using various sets of RPWB items, we found very high factor correlations among the dimensions of well-being, especially personal growth, purpose in life, self-acceptance, and environmental mastery. That is, the six-factor model makes theoretical claims that do not yield large or consistent empirical distinctions when standard measures and instrumentation are used. Where Ryff and Singer’s comment (Best News Yet on the Six-Factor Model of Well-Being. 2006. Social Science Research 35) refers directly to that analysis, their methodological discussion is most often irrelevant or incorrect. Their text largely ignores and fails to challenge our strong empirical findings about the factorial structure of well-being. In this response, we reinforce these findings and their implications for the (in)validity of the six-factor well-being model as implemented by Ryff. We also explain why Ryff and Singer’s lengthy review of studies that show differential relationships of RPWB factors with other variables should be interpreted with far greater caution than Ryff and Singer recognize. We offer recommendations for analyzing RPWB items in surveys that have already been conducted, but we also emphasize the need for a thorough rethinking of the measurement and dimensionality of psychological well-being.     

The cross-country and cross-time measurement invariance of positive and negative affect scales: Evidence from European Social Survey

Survey-based measures of subjective well-being are increasingly often analyzed cross-culturally. However, international comparison of these measures requires measurement invariance. Therefore, the major goal of this study is to investigate the cross-country and cross-time comparability of the 4-item positive and 7-item negative affect scales used in European Social Survey Round 3 (2006) and Round 6 (2012). This study applies both the traditional exact and the more recent Bayesian approximate approach to assess whether the affect scales are measurement invariant. The approximate approach detected several non-invariant items that are problematic for cross-national comparison and should be dropped from the scales. Consequently, measurement invariance was established in all countries over the two rounds for the reduced scales, allowing researchers to meaningfully compare their latent mean scores and the relationships with other theoretical constructs of interest. Thus, the study highlights the advantages of using multiple indicators and the necessity of measurement invariance testing in subjective well-being research.     

Understanding selection bias,time-lags and measurement bias in secondary data sources: Putting the Encyclopedia of Associations database in broader context

Secondary data gathered for purposes other than research play an important role in the social sciences. A recent data release has made an important source of publicly available data on associational interests, the Encyclopedia of Associations (EA), readily accessible to scholars (www.policyagendas.org). In this paper we introduce these new data and systematically investigate issues of lag between events and subsequent reporting in the EA, as these have important but under-appreciated effects on time-series statistical models. We further analyze the accuracy and coverage of the database in numerous ways. Our study serves as a guide to potential users of this database, but we also reflect upon a number of issues that should concern all researchers who use secondary data such as newspaper records, IRS reports and FBI Uniform Crime Reports.     

Intergenerational effects of shifts in women’s educational distribution in South Korea: Transmission, differential fertility, and assortative mating

This study examines the intergenerational effects of changes in women’s education in South Korea. We define intergenerational effects as changes in the distribution of educational attainment in an offspring generation associated with the changes in a parental generation. Departing from the previous approach in research on social mobility that has focused on intergenerational association, we examine the changes in the distribution of educational attainment across generations. Using a simulation method based on Mare and Maralani’s recursive population renewal model, we examine how intergenerational transmission, assortative mating, and differential fertility influence intergenerational effects. The results point to the following conclusions. First, we find a positive intergenerational effect: improvement in women’s education leads to improvement in daughter’s education. Second, we find that the magnitude of intergenerational effects substantially depends on assortative marriage and differential fertility: assortative mating amplifies and differential fertility dampens the intergenerational effects. Third, intergenerational effects become bigger for the less educated and smaller for the better educated over time, which is a consequence of educational expansion. We compare our results with Mare and Maralani’s original Indonesian study to illustrate how the model of intergenerational effects works in different socioeconomic circumstances.