Melissa G Wolf, PhD ABD

TEACHING EXPERIENCE

Teaching Assistant at University of California, Santa Barbara (2019 – 2021)
ED214A: Introduction to Statistics (2x)
ED214B: Inferential Statistics (2x)
ED214C: Linear Models
SOC108: Introduction to Research
UCSB-Smithsonian Scholars Program: Introduction to Data Science

Teaching Assistant at University of Maryland, College Park (2010 – 2012)
EDMS645: Quantitative Methods
EDMS610: Classroom Assessment

Publications

1. McNeish, D. & Wolf, M. G. (accepted). Dynamic fit index cutoffs for one-factor models. Behavior Research Methods.

2. Boness, C.L., Helle, A.C., Miller, M.B, Wolf, M.G., & Sher, K.J. (accepted). Who opts in to alcohol feedback and how does that impact behavior? A pilot trial. Journal of Studies on Alcohol and Drugs.

3. Wolf, M. G., Ihm, E., Maul, A., & Taves, A. (2022). Survey item validation. In S. Engler & M. Stausberg (Eds.), Handbook of Research Methods in the Study of Religion (2nd ed.). Routledge.

4. McNeish, D. & Wolf, M. G. (2021). Dynamic Fit Index Cutoffs for Confirmatory Factor Analysis Models. Psychological Methods. https://doi.org/10.1037/met0000425

5. Clairmont, A., Wolf, M. G., & Maul, A. (2021). The prevention and detection of deception in self-report survey data. In U. Luhanga & G. Harbaugh (Eds.), Basic Elements of Survey Research in Education: Addressing the Problems Your Advisor Never Told You About. Charlotte, NC: Information Age Publishing.

6. McNeish, D., & Wolf, M.G. (2020). Thinking twice about sum scores. Behavior Research Methods. https://doi.org/10.3758/s13428-020-01398-0

7. Luo, Y. & Wolf, M. G. (2019). Item parameter recovery for the two parameter testlet model with different estimation methods. Psychological Test and Assessment Modeling, 61(1), 65-89.

8. Ghafoori, B., Wolf, M. G., Nylund-Gibson, K., & Felix, E. D. (2019). A naturalistic study exploring mental health outcomes following trauma-focused treatment among diverse survivors of crime and violence. Journal of Affective Disorders, 245, 617–625. https://doi.org/10.1016/j.jad.2018.11.060

9. Raines, T.C., Gordon, M., Harrell-Williams, L.M., Diliberto, R.A, & Parke, E.M. (2017). Adaptive skills and academic achievement in Latino students. Journal of Applied School Psychology, 245 - 260. https://doi.org/10.1080/15377903.2017.1292974

10. Gordon, M., VanderKamp, E. & Halic, O. (2015). Research brief: International Baccalaureate programmes in Title I schools in the United States: Accessibility, participation and university enrollment. https://www.ibo.org/globalassets/publications/ib-research/title-1-schools-research.pdf

11. Bergeron, L. & Gordon, M. (2015). Establishing a STEM pipeline: Trends in male and female enrollment and performance in higher level STEM courses. International Journal of Science and Mathematics Education, 1 - 18. http://dx.doi.org/10.1007/s10763-015-9693-7

12. Gordon, M., & Bergeron, L. (2014). The use of multilevel modeling and the level two residual file to explore the relationship between Middle Years Programme student performance and Diploma Programme student performance. Social Science Research, 50, 147-163. https://doi.org/10.1016/j.ssresearch.2014.11.004

Under Review

1. Wolf, M. G. & Denison, A. (under review). Survey uses may influence survey responses.

2. Wolf, M. G. & McNeish, D. (under review). dynamic: An R package for deriving dynamic fit index cutoffs for factor analysis.

Packages and Applications

1. Wolf, M. G. & McNeish, D. (2020). Dynamic Model Fit (version 0.1.0.). [Software]. Available from www.dynamicfit.app

2. Wolf, M. G. & McNeish, D. (2020). dynamic: Model fit cutoffs. R package version 0.1.0. https://cran.r-project.org/web/packages/dynamic/index.html

Select First Author Presentations

1. Wolf, M. G. & McNeish, D. (2022, April). Dynamic Model Fit Indices: A R Shiny Application. In D. Katz (Chair), Past, Present, and Future of Model Fit: Modern Solutions to Historical Challenges. Symposium to be conducted at the annual meeting of the American Educational Research Association.

2. Wolf, M. G., Ihm, E., Katz, D., & Maul, A. (2020, June). Improving Psychological Measurement: Introducing the RPE Method. Workshop presented at the annual meeting of the Society for the Improvement of Psychological Science, Virtual Meeting.

3. Wolf, M. G. (2020, April). The Response Process Evaluation Method. Paper presented at the meeting of the International Objective Measurement Workshop, San Francisco, CA.

4. Wolf, M. G. & Ihm, E. (2019, November). Validation Methods and Results of the Inventory of Non-Ordinary Experiences (INOE). In C. Kravette (Chair), Comparing Non-Ordinary Experiences across Cultures: Methodological Innovations and Findings from the US and India. Symposium conducted at the annual meeting of the American Academy of Religion.

5. Wolf, M. G., Clairmont, A., Maul, A., Furlong, M. J., & Stiblina, V. (2019, April). A Method for Detecting Invalid Responses. Paper presented at the annual meeting of the American Educational Research Association, Toronto, Canada.

6. Wolf, M. G., Nylund-Gibson, K., Dowdy, E., & Furlong, M. J. (2019, April). A comparison of categorical and continuous latent variable models in a moderation framework. In O. Simon (Chair), Mixture Modeling in Practice. Symposium conducted at the annual meeting of the American Educational Research Association, Toronto, Canada.

7. Wolf, M. G., & Bergeron, L. (2018, November). Using different data sources to address the same research questions: Evaluating the effectiveness of new curriculum on student outcomes. Paper presented at the annual meeting of the California Educational Research Association, Anaheim, CA.

8. Wolf, M. G. (2018, April). Validation in the absence of traditional constructs. Paper presented at the meeting of the International Objective Measurement Workshop, New York, NY.

Leadership

• American Educational Research Association Division D Program Committee Graduate Student Representative, 2018 – 2019
• Expert Advisory Board member at the Center for Mind and Culture, 2019 – Present
• Course Director: Psychological Network Analysis, 2019
• Research Methods and Statistics Student Association President, 2015 – 2016

Membership

• [Society for the Improvement of Psychological Science] (https://improvingpsych.org/)
• [American Educational Research Association] (https://www.aera.net/)
  • Division D, Survey Research in Education SIG
• [National Council on Measurement in Education] (https://www.ncme.org/home)

Manuscript Reviewing

• Interdisciplinary Journal of Problem-Based Learning
• Meta-Psychology
• Behavior Research Methods

Honors and Awards

• Block Grant Dissertation Award, University of California, Santa Barbara (2020)
• Department of Education Excellence Award for Research (2019)
• Grad Slam Finalist (Top 9 out of 79) (2019)
• Block Grant Fellowship Award, University of California, Santa Barbara (2018)
• Education Travel Grant, University of California, Santa Barbara (2018–2019)
• New Tech Network $10,000 Research Grant, Napa, CA (2016)
• Block Grant Fellowship Award, University of California, Santa Barbara (2016)
• University of Denver Graduate Student Travel Grant (2016)
• University of Denver Scholarship Award (2015)
• Dean’s Fellowship, University of Maryland, College Park (2010–2011)

Coursework

Structural Equation Modeling, Constructing Measures, Analyzing and Validating Measures, Item Response Theory, Psychological Network Analysis, Psychometrics, Bayesian Statistics, Mixture Modeling, Multi-Level Modeling, Causal Inference, Meta-Analysis, Empirical Research Methods, Program Evaluation, Applied Sampling, Survey and Design Analysis, Philosophy of Measurement, Introduction to SAS, Introduction to Simulation, Multivariate Data Analysis, Applied Measurement, Factor Analysis, Quantitative Research Methods I & II, Applied Multiple Regression Analysis, Classroom Assessment & Evaluation, Introduction to Qualitative Research, Ethnography, Anthropology of Education, Social Psychology