Using National Longitudinal Data to Examine Spatial Variation in Gendered School-to-Work Linkages: Mediation With Nested Regression Models

Abstract

This case study details the first data analysis project I completed when I started graduate school. Our study investigated if men and women benefited from high schools offering career and technical training for blue-collar jobs in communities where this type of work is still prevalent. We used a longitudinal national dataset to examine the connection between the local labor market, high school coursework, and student postsecondary and labor market outcomes. This case study traces the life of a research project-how to turn research questions into models, how to turn concepts into variables, and how to present your results. This case also discusses how to deal with issues of selection that arise when using different models across waves of longitudinal data and how to measure mediation using nested models with logistic regression.

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