About Me

Overview

I am an associate professor of sociology, co-director of advanced methodologies, and co-director of the Kernan experimental social science lab at Purdue University. My research and education spans sociology, psychology, and statistics. I am a quantitative methodologist with work on categorical data analysis, experimental design, and latent variable modeling. My substantive work focuses on gender and sexuality and the social factors that affect health and well-being. Both my substantive and methodological work includes a diverse array of quantitative methods including survey experiments, lab experiments, representative survey data, longitudinal surveys, and simulation-based approaches.

My work has appeared in the American Sociological Review, Social Problems, Sociological Methodology, Social Psychology Quarterly, Sociological Science, Social Science & Medicine, Social Science Research, Journal of Marriage and Family, and other peer-reviewed journals. My research has been supported by the National Science Foundation, the Russel Sage Foundation, Time-Sharing Experiments for the Social Sciences (TESS), the Kinsey Institute, the American Sociological Association’s social psychology section, and others.

I am firmly committed to open science and reproducibility. Thus, I freely share the data, code, and replication files for all of my research projects as well as for all courses, seminars, and workshops I teach.

Research on Quantitative Methodology

My work on categorical data analysis seeks to expand analysis, interpretation, and visualization tools for these models. For example, I have published on statistical approaches for testing nonlinear interaction effects and visualization tools for interpretation. Another project develops a general framework for examining cross-model comparisons of predictions and effects (across both linear and nonlinear models). A current project expands these approaches to random, fixed, and mixed effects models. A new line of research develops methods for summarizing the effects of nominal independent variables in linear and nonlinear models.

Another active area of my methodological research focuses on experimental design. A recent article overviews the use of the experimental method in the social sciences and lays out directions for the future—including a new framework of purposive sampling that encourages studying more diverse populations. Multiple projects examine new and old approaches for measuring interpersonal status in groups, including developments for studying groups online. A new project examines how we measure stereotypes and cultural beliefs, and the role of dominant groups in setting cultural common knowledge.

Latent variable models for categorical items (e.g., item response theory models) present similar interpretation challenges to categorical data analysis models. Multiple current projects develop new tools for understanding these models. One offshoot of this work develops a new test of item bias, allowing for tests of whether specific items are biased against particular groups.

I also write statistical software to implement the new statistical approaches I develop (primarily using Stata). Available programs/packages/commands implement best practices for data visualization, ways to visualize imbalance across groups, easy ways to produce publication quality descriptive statistics tables, and statistical tests of mediation. I am currently working on programs (a) that simplify tests of cross-model comparisons, (b) that provide new approaches for interpreting item response theory models, and (c) that calculate measures of model fit in latent class analysis.

Research on the Intersections of Gender and Sexuality 

I use social psychological theories of status, identity, and stereotyping to better understand the intersections of gender and sexuality. Much of this work focuses on inequalities in the labor market. For example, I have published on wage inequalities based on sexual orientation and on gender inequalities in leadership positions. I am currently working on multiple projects examining parental leave: e.g., how an organization’s parental leave policies influence workplace outcomes for those who take parental leave and how parental leave-taking affects perceptions of good parenting. A new line of this work focuses on differences between married heterosexual parents, gay and lesbian parents, and single parents.

Multiple projects of mine examine stereotypes of gender and sexual orientation—and the consequences of these stereotypes. One project shows a shift to more traditional attitudes about gender and parenting during the pandemic. 

Much of my work focuses on how status and identity influence self- and other-categorization. E.g., One project examines how status processes affect who gets labeled as what sexual orientation category. Another project shows how social and structural factors explain rates of sexual identity disclosure across groups and social contexts.  

Research on Health & Well-Being

Health behaviors—such as substance use, exercise, and dietary habits—are a product of both personal choices but also structural constraints and social influence. For example, I have shown that the accumulation of different types of social roles influences health behavior practices. A current project examines both between- and within-gender differences in health behavior.

Mental health is similarly affected by social factors. For example, the number and types of social roles someone occupies has important effects on mental health. A current project examines (potential) differential effects of role-accumulation across the life course. Another project shows that sexual identity-behavior discrepancies (i.e., someone behaves in ways inconsistent with their identity) have myriad detrimental effects on mental health. 

In another line of work I detail how the meaning of mental health labels themselves are socially patterned, with the connotations of fear they carry moderating the effects mental illness labels have on how someone is subsequently treated by others.

Teaching

I primarily teach applied statistics and quantitative methods courses and short workshops on advanced quantitative methods. I teach Statistical Horizons/Code Horizons seminars on categorical data analysis, data visualization using Stata, missing data using Stata (coming soon), and Stata programming (coming soon). 

I teach semester-long graduate courses on categorical data analysis, experimental design, latent variable modeling, and social psychology. I also teach one and two-day workshops on data visualization (in Stata and R), survey design, analysis with missing data, workflow practices for reproducible research, statistical programming in Stata, survey experiments, and on advice for teaching methodology courses. The materials for these courses and workshops are freely available under the Teaching tab.

Contact Information

PDFs of all of my published articles are available on the Research page of this site.

Feel free to email me if you have questions: tmize@purdue.edu

You can also follow me on Twitter @MizeTrenton