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I am a quantitative and applied-experimental methodologist who pursues two streams of programmatic research. My main research stream uses quantitatively advanced methods to investigate medical, educational, and mental health disparities in the child and maternal health population. I use latent variable models like item response theory (IRT), confirmatory factor analysis (CFA), and structural equation modeling (SEM) to examine the reliability and validity of measures across traditionally underserved and underrepresented groups (e.g., US minorities). In this research, I aim to understand measurement bias' impact on efforts to understand and eliminate disparities. I also seek to elucidate the mechanisms leading to measurement bias. Given that much of my work involves large samples (e.g., n's ranging from 100,000 to 400,000), I perform methodological research developing new techniques for evaluating the practical impact of statistically significant measurement bias.
In my main program of research, I also use multilevel models to better understand individual and contextual level influences on medical, educational, and behavioral outcomes. These models include hierarchical linear models, generalized hierarchical linear models, longitudinal growth models, and multilevel structural equation models. I am especially interested in extending "traditional" multilevel modeling techniques to complex sampling designs. These designs present unique challenges when using multilevel models. Thus, in addition to uniquely applying multilevel models in complex survey data, I am involved in research developing and describing methods for using multilevel models in complex sampling designs. Currently, I am focused on advancing methods for handling design weights in multilevel models.
My second stream of research examines the application and evaluation of psychological theories of the science of learning in young adulthood. My work focuses on evaluating new technologies, techniques, and strategies that should: bolster young adults' understanding of scientific methods and support students' long term retention and application of scientific thinking throughout adulthood. I work to develop and psychometrically evaluate measures of scientific thinking and student engagement. I also endeavor to understand what leads to effective teaching among college students. As with all my research, this program uses latent variable models and multilevel models to better uncover intricate relationships among variables across individual, contextual, and social levels.
In sum, as a methodologist I am particularly interested in developing and uniquely applying quantitative methods to better understand individual and contextual level influences on medical, educational, and physical and mental health disparities in the child and maternal health population. I am interested in applying rigorous quantitative and psychometric methods to better understand and evaluate the development of scientific thinking. I am someone with a passion for quantitative research understood within broad social and cultural contexts. This passion results in an active research lab that includes undergraduate and graduate research assistants.
If you would like to apply for one of my lab's spots, please email me a copy of your vitae, the courses you've taken (including your grades), and a two page single-spaced personal statement that describes your personal, academic, and professional goals. In your personal statement, please describe your area of interest in psychology or its allied disciplines, why you would like to work with me, and what you expect this experience will bring you. Additionally, please address what excites you about research. I look forward to hearing from you!
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