I am currently a second year Ph.D candidate in the Quantitative Psychology program at the University of Virginia. I am working in the Mathematical Psychology Lab, where Timo von Oertzen is my advisor. I also spend time working in the Social Development Lab in the Curry School of Education with my secondary advisor, Sara Rimm-Kaufman, and in the Implicit Social Cognition Lab with Brian Nosek. I earned bachelor degrees in Applied Mathematics and Psychology from the University of Rhode Island, and plan to develop these interests further in graduate school.

Department of Psychology, University of Virginia

Research Methods & Data Analysis I Lab, Fall 2012
Department of Psychology, University of Virginia
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Honors Quantitative Methods in Psychology, Spring 2011
Department of Psychology, University of Rhode Island

URI 101 Co-Instructor, Fall 2010
Office of Internships and Experiential Education, University of Rhode Island

Manuscripts

Duerr, S., Harlow, L. L., Martin, D., Baird, G. L., & Poindexter, B. (submitted). Investigating multivariate statistical inference methods and procedures in APA journals. Psychological Methods.

Conference Posters

Martin, D., von Oertzen, T., Smyth, F., Melcher, T., & Mitrea, I. (2013, May). Implicit math gender stereotypes changing over time: An application of latent growth curve modeling. Poster to be presented at the 25th annual meeting of the Association for Psychological Science, Washington, D.C.

Duerr, S. R., Baird, G. L., & Martin, D. (2013, May). Is psychology a science? Lessons from The Batman. Poster to be presented at the 25th annual meeting of the Association for Psychological Science, Washington, D.C.

Duerr, S., Harlow, L. L., Trandafir, E., Martin, D., Baird, G., & Poindexter, B. (2012, August). Data harvesting: Streamlining the collection of data for meta-analysis and methodological reviews of literature. Poster presented at the 120th annual meeting of the American Psychological Association, Orlando, FL.

Harlow, L. L., Duerr, S., Martin, D., Fidler, F., & Cumming, G. (2011, August). Multivariate inferences in APA journals: Patterns and guidelines. Presented at the 119th annual conference of APA, Washington, D.C.

Martin, D. & Rimm-Kaufman, S. E. (2013, February). How teacher attitudes relate to fidelity of implementation of the Responsive Classroom approach. Poster presented at the Curry Research Conference, Charlottesville, VA.

Martin, D. (2012, November). A person-centered approach to measuring mathematics attitudes and self-concepts: An application of latent class analysis. Presented at Design and Data Analysis (DADA), Charlottesville, VA.

Assessing Teacher Training Programs

My experiences as a mathematics tutor and teaching assistant at the University of Rhode Island has made me interested in developing better teaching methods for statistics/math as well as the understanding the current state of STEM education in schools. To gain such substantive experience, I collaborate with Dr. Sara Rimm-Kaufman's Social Development Lab in the Curry School of Education to assess the Responsive Classroom approach as it relates to math achievement in elementary school children. I am currently working on an independent project to see how teachers' attitudes and beliefs affect their fidelity of implementation of this approach.

STEM Engagement in College Mathematics

Success in college mathematics is essential for a strong STEM workforce as such classes are "pipelines" to the hard-science disciplines. Many projects on STEM engagement involve the assessment of instructional methods and/or explicit psychological measures, but do not take into account implicit measures of bias (i.e. associating math-male significantly more than math-female) that still pervade our culture. I am currently collaborating with Brian Nosek and Fred Smyth on the Full Potential Initiative to better understand how these implicit biases in the college environment may be related to shaping personal identities and contributing to an individual's intent to stay involved in STEM-related classes and other activities.

Exploratory Data Analysis for Longitudinal Data

The incorporation of exploratory longitudinal analysis techniques, namely identifying hetereogeneous sub-populations based on longitudinal trajectories, can provide new avenues to answer theoretically interesting research questions that often remain unanswered after traditional confirmatory measures have already been exhausted. While many techniques of varying complexity exist, it can be difficult to determine which methods work best in what situations. My pre-dissertation involves comparing these methods on simulated data across a number of varying dataset conditions, such as number of sub-groups, statistical noise, effect size of parameters, etc., to determine: 1) Which methods are superior in what situations? and 2) Under what circumstances are more complex modeling techniques better than more parsimonious ones?

How Multivariate Analyses are Reported in APA journals

With Dr. Lisa Harlow (undergraduate advisor), and Sunny Duerr (PhD candidate in behavioral psychology at the University of Rhode Island), I am continuing research from my undergraduate on an analytical summary of multivariate methodology in seven American Psychological Association (APA) journals with high impact ratings. These findings allow us to view the current statistical paradigm in various areas of psychology and could serve as a helpful resource tool for all psychologists involved in research. We plan to publish the results comparing the 2009 and 2011 journals, hoping to capture effects from the release of the 6th edition of the APA publication manual that cites the need for additional measures of statistical inference beyond significance testing, such as utilizing effect sizes and confidence intervals.