Investigating the Interdependencies of “Troubles in America”

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Contributed Abstract 

Speed 

Md Mahedi Hasan (1), Wooyoung Kim (2), Jacqueline Carlton (2), David Rice (3), Daryl DeFord (1)

(1) Washington State University, N/A, (2) N/A, N/A, (3) Western Washington University, N/A

Wooyoung Kim  
N/A

Jacqueline Carlton  
N/A

David Rice  
Western Washington University

Daryl DeFord  
Washington State University

Md Mahedi Hasan  
Washington State University

Jacqueline Carlton  
N/A

In this cross-sectional study, we study interdependencies among risk factors faced by the American population, drawing on data from the most recent wave of the General Social Survey. Our exploration is motivated by the findings of Smith (2005), who examined dimensions of "troubles in America," placing them into 8 categories including health, work, and finances. Our research explores the hypothesis that difficulties experienced in one domain may influence outcomes in others. Using Structural Equation Modeling (SEM) and leveraging the substantial volume of survey responses, we are able to study the intricate relationships between these domains. We represent each domain as a latent variable with multiple observed indicators, allowing for a nuanced understanding of the interactions. Our model integrates standard control variables to address potential confounders, enabling thorough assessment of interdependence. This framework allows us to explore covariances between domains, uncovering potential connections and dependencies. To extend this work, we also conduct an ordinal SEM analysis, investigating the relationship between our latent factors and overall reported happiness.

Structural Equation Modeling (SEM)|Cross-sectional|Latent factors|Interdependence|Survey|General Social Survey (GSS)

Section on Statistical Computing

Data Science