MELISSA L. MCTERNAN
My research interests include methods for analysis of longitudinal non-normal data. Specifically, I have focused on methods for data with a high proportion of zeros, and categorical and continuous positively skewed data. I study methods best-suited for handling such data, including random-effects and multi-level models. I also have expertise in survival analysis, factor analysis, and missing data. Because of my methods and statistics expertise, I often collaborate on substantive research projects, as well. In this vein, I specialize and often collaborate on projects that include applications to social and political empowerment as well as health outcomes.
Blozis, S.A., McTernan, M., Harring, J., & Zheng, Q. (In Press, Jan 2020). Two-part Mixed-effects Location Scale Models. Behavior Research Methods.
McTernan, M., Yokoo, K., & Tong, W. (In Press, Dec 2019). Gender-affirming Chest Surgery on Non-binary versus Transmasculine Patients. Annals of Plastic Surgery.
McTernan, M. (2017). An Advanced Study of Methods for Categorical and Continuous Data with Many Zeros (Doctoral dissertation, University of California, Davis).
Davoudzadeh, P., McTernan, M., & Grimm, K. J. (2015). Early school readiness predictors of grade retention from kindergarten through eighth grade: A multilevel discrete-time survival analysis approach. Early Childhood Research Quarterly, 32, 183-192.
McTernan, M., Love, P., & Rettinger, D. (2014). The influence of personality on the decision to cheat. Ethics & Behavior, 24(1), 53-72.
McTernan, M., & Blozis, S. User-specified likelihood expressions using NLMIXED and the GENERAL statement (White paper for a conference presentation at the Western Users of SAS Software 2013 Regional Convening).
Hello, thank you for visiting my page! This site is primarily dedicated to my professional life, so I will share with you a little more about that. I am a doctor of Quantitative Psychology, meaning that I am trained in the study of methods for collecting, managing, and statistically analyzing data in the social and behavioral sciences. I studied at UC Davis with Dr. Shelley Blozis, and completed my doctoral training in January 2017. In the Fall of 2017 I joined the faculty at Sacramento State as an Assistant Professor of Quantitative Methods in the Psychology Department. In December 2019 I made the difficult decision to leave this position and change careers. Most currently, I am a Research Statistician at Boston College in Boston, Massachusetts, supporting faculty across the campus in their statistical analyses related to research. I am also teaching a course in Graduate Statistical Methods to PhD students at Clark University in Worcester, MA.
As a quantitative psychologist, my research has covered topics such as advanced methods for analyzing categorical and continuous data with many zeros, mixed-effects modeling, and an applied study in which we used a multilevel survival model to predict grade retention. Click here for a complete list of research and publications.
As a Quantitative Psychologist, I often teach statistics and research methods courses. Teaching these courses has always been a welcomed challenge for me. I understand that many students come to the psychology discipline with little interest in statistics. Throughout my time with the students, I strive to 1) impart a deep understanding of statistical concepts, 2) draw connections from the material that will incite excitement about the subject matter, and 3) to empower the students to use statistics as a tool to explore research questions of their own. I structure my classroom to reflect these goals.
PSYCHOLOGY 121 @ Sac State:
METHODS AND STATISTICS FOR PSYCHOLOGICAL RESEARCH
Project-based experience of Psychology. Study of scientific processes in research such as literature reviews; developing testable hypotheses; design; IRB review; data collection, analysis, and interpretation; critical analysis of studies; APA paper preparation; and issues in dissemination. Study of some advanced statistical processes such as factorial ANOVAs, planned and post hoc comparisons, and multiple regression. Study of statistical software programs used in the analysis of data. Prerequisite: PSYC 9
PSYCHOLOGY 302 @ Clark:
GRADUATE STATISTICAL METHODS
Note: I enjoy teaching and mentoring all students. To facilitate my ability to create a safe learning space for my students, I have completed the following trainings, in addition to :
LGBTQIA Safe Zone Training (CSUS)
Trans* Safe Zone Training (UC Davis)
Dreamer Ally Training (CSUS)
PSYCHOLOGY 9 @ Sac State:
STATISTICS FOR PSYCHOLOGY
Introduction to descriptive and inferential statistics as tools for evaluating data from Psychological research. Topics include: measures of central tendency, measures of variability, correlation and regression, sampling distributions, hypothesis testing procedures including t-tests and analysis of variance, and selected other topics. Application of hand computation will be emphasized to include the interpretation and significance of statistical findings. Prerequisite: Passing score on ELM; PSYC 2, PSYC 4, PSYC 8. PSYC majors only.