Broadly, my research has focused on three substantive areas related to US health and mortality, with specific attention given to the social origins of the disease and mortality patterns we observe in the US population: 1) long-term trends in race/ethnic disparities in all-cause and cause-specific adult mortality rates, and the social, political, and economic conditions that shape these disparities, 2) the association between the US obesity epidemic and adult mortality rates, and the increasing effect that obesity has on US longevity, and 3) the long-term health effects of early-life adversity. I have also grown increasingly interested in the methodological approaches to addressing all three of these substantive areas of quantitative inquiry. As such, some of my recent work has been focused on advancing new ways to address these questions with statistical techniques.
life course, health, mortality, social demography, quantitative methods
SOCY 2061 - Introduction to Social Statistics
Fall 2018 / Spring 2019 / Spring 2020 / Spring 2021
Introduces students to quantitative analysis of social phenomena. Emphasizes understanding and proper interpretation of graphs; measures of central tendency, dispersion, and association; and the concept of statistical significance. Assumes students have only limited mathematical background.
SOCY 6111 - Data 2: Data Analysis
Fall 2018 / Fall 2019
Introduces students to mainstream multivariate regression techniques used in the social sciences. The majority of the course focuses on the Ordinary Least Square model and on the extension of this model to nominal, ordinal and count dependent variables. Students analyze data of their choosing with statistical software packages including SPSS, SAS, and STATA. Department prerequisite: SOCY 5111 or equivalent.
SOCY 7111 - Data III--Advanced Data Analysis
Denotes third graduate course in sequence of quantitative methods. Following basic inferential statistics (SOCY 5111) and multivariate regression analysis (SOCY 6111), students study advanced statistical techniques such as event history analysis, multilevel modeling, structural equation modeling, and latent class analysis. May be repeated up to 9 total credit hours when topics vary.