Abstract
This chapter describes the two main quantitative strategies for explaining the association of mental or emotional well-being with various social and social psychological circumstances or characteristics, such as level of education, identity, or personal history. Statistically explaining an association means demonstrating the conditions under which it no longer exists. If an association vanishes under specific conditions, then the absence of those conditions accounts for the association. Data analysts have two basic methods for explaining associations. Progressive adjustment looks for mediators, which are consequences of the independent variable that cause the outcome, forming a bridge between them. Interaction analysis looks for moderators, which regulate the size and direction of the association being analyzed. External moderators apply to everyone whereas internal moderators apply only to people in a limited range of the independent variable. The same explanatory variable can be both mediator and moderator, as illustrated in the case of structural amplification.
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Abbreviations
- EXP:
-
Exponent
- LN:
-
Natural logarithm
- SQRT:
-
Square root
- VIF:
-
Variance Inflation Factor
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Acknowledgments
Data collection, analysis, and reporting were supported by two grants from the National Institute on Aging: R01 AG12393 “Aging, Status and the Sense of Control” (Mirowsky Principal Investigator (PI), Ross Co-PI), and R01 AG035268 “Reconceptualizing Socioeconomic Status and Health” (Ross PI, Mirowsky Co-PI).
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Mirowsky, J. (2013). Analyzing Associations Between Mental Health and Social Circumstances. In: Aneshensel, C.S., Phelan, J.C., Bierman, A. (eds) Handbook of the Sociology of Mental Health. Handbooks of Sociology and Social Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4276-5_8
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DOI: https://doi.org/10.1007/978-94-007-4276-5_8
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