Department of Psychology
Quant Mentoring Committee
About
The quantitative mentoring committee serves the department of psychology at UCR by providing mentoring in quantitative methods and software to graduate students and faculty. We provide both individual consultations and long-term guidance, offering support with everything from quick coding questions to more in-depth statistical issues.
The committee is comprised of the following members:
- Dr. Holly O’Rourke (hollyo@ucr.edu)
- Dr. Daniel Ozer (dozer@ucr.edu)
- Dr. Stephen Antonoplis (stephen.antonoplis@ucr.edu)
- Dr. Tabea Springstein (tabea.springstein@ucr.edu)
- Minghui Wang, graduate member (minghui.wang@email.ucr.edu)
- Arash Mehrkesh, graduate member (arash.mehrkesh@email.ucr.edu)
The Process of Getting Help
To help us assist you efficiently, we request that you adhere to the following procedures when reaching out for assistance.
- For graduate students: Please reach out to either of our graduate committee members (Arash and Minghui) to schedule a meeting. Depending on the topic and depth of your question, you’ll be referred to the appropriate committee member.
- For faculty: Please reach out to Holly (the committee chair), who will assist you or connect you with someone who can, or you may contact any of the faculty listed below for questions about specific methods or software.
- For coding issues, please include:
- A screenshot of your code and/or the error message
- For statistical questions, please include:
- A concise but complete description of your research question
- List of variables and how they’re measured
- Your intended analyses
- The specific question you’d like help with
- Any additional information about your study design, sample size, or preliminary analyses that you’re willing to share can also be very helpful.
Methods and software expertise
The committee is happy to field your questions about anything and everything, but we recognize that the department contains a wealth of knowledge about quantitative methods and software beyond the committee’s expertise. We have compiled a list of methods and software that may be helpful in connecting directly with a faculty member who has expertise in that area.
| Data Analysis Method | Faculty with Expertise |
|---|---|
| 2-photon imaging data analysis | Deepa Ramamurthy |
| Age-period-cohort analysis | Olivia Atherton |
| Bayesian cognitive modeling | Ian Ballard |
| Bayesian estimation | Kevin Esterling (Political Science) |
| Bayesian hierarchical modeling | Weiwei Zhang |
| Causal inference | Kevin Esterling (Political Science), Soojin Park (Education) |
| Computational modeling | Ian Ballard |
| Diffusion-weighted imaging (DWI) analysis | Ilana Bennett |
| Dyadic data analysis | Megan Robbins |
| EEG data analysis | Halle Dimsdale-Zucker, Gene Brewer |
| Event Related Potentials (ERPs) data analysis | Weiwei Zhang |
| Experimental design for interventions | Holly O'Rourke |
| Experimental design for social psychology | Kate Sweeny |
| Experimental design in behavioral neuroscience | Deepa Ramamurthy, Brent Hughes |
| Eye tracking data analysis | Weiwei Zhang, Gene Brewer, Na Yeon Kim |
| Factor analysis | Holly O'Rourke, Gene Brewer, Daniel Ozer, Stephen Antonoplis |
| fMRI data analysis | Weiwei Zhang, Halle Dimsdale-Zucker, Brent Hughes, Ian Ballard, Na Yeon Kim, Ilana Bennett |
| Integrative data analysis | Olivia Atherton |
| Intensive longitudinal data analysis | Tabea Springstein, Holly O'Rourke |
| Language models | Brent Hughes |
| LASSO regression | Holly O'Rourke |
| Latent change score models | Holly O'Rourke |
| Latent growth curve models | Holly O'Rourke, Cecilia Cheung, Olivia Atherton |
| Longitudinal study design | Olivia Atherton, Holly O'Rourke |
| Machine learning | Holly O'Rourke, John Franchak, Ian Ballard, Soojin Park (Education) |
| Mathematical modeling | Weiwei Zhang |
| Maximum likelihood estimation | Kevin Esterling (Political Science) |
| Measurement invariance | Cecilia Cheung, M. Alejandra Arce, Stephen Antonoplis |
| Mediation analysis (causal) | Soojin Park (Education) |
| Mediation analysis (traditional) | Holly O'Rourke |
| Meta-analysis | Olivia Atherton |
| Multilevel modeling | Tabea Springstein, Cecilia Cheung, Olivia Atherton, Holly O'Rourke, Brent Hughes, Stephen Antonoplis |
| Multinomial Processing Tree Modeling | Jimmy Calanchini |
| Network analysis | Holly O'Rourke, Brent Hughes |
| Psychometric curve fitting | John Franchak |
| Psychometrics | Stephen Antonoplis, Daniel Ozer |
| Pupillometry | Gene Brewer |
| Secondary data analysis | Olivia Atherton |
| Social network analysis | Stephen Antonoplis |
| Spiking data analysis | Deepa Ramamurthy |
| Structural equation models | Holly O'Rourke, Cecilia Cheung, Stephen Antonoplis, M. Alejandra Arce, Daniel Ozer, Olivia Atherton |
| Survival analysis | Olivia Atherton |
| Time series analysis | Holly O'Rourke |
| Software | Faculty with Expertise |
|---|---|
| AFNI | Na Yeon Kim |
| fmriprep | Ian Ballard |
| Freesurfer | Ian Ballard |
| FSL | Ian Ballard, Na Yeon Kim, Ilana Bennett |
| GitHub/git | Holly O'Rourke, John Franchak, Halle Dimsdale-Zucker |
| JAGS | Kevin Esterling (Political Science) |
| JASP | Gene Brewer |
| Julia | John Franchak |
| Mathematica | Holly O'Rourke |
| MATLAB | John Franchak, David A. Rosenbaum, Na Yeon Kim |
| Mplus | Holly O'Rourke, Cecilia Cheung, Olivia Atherton, M. Alejandra Arce |
| MultiBUGS | Kevin Esterling (Political Science) |
| Prism | Ilana Bennett |
| Python | Holly O'Rourke, Halle Dimsdale-Zucker, Kevin Esterling (Political Science), Ian Ballard, Na Yeon Kim |
| R | Holly O'Rourke, John Franchak, Halle Dimsdale-Zucker, Olivia Atherton, Gene Brewer, Stephen Antonoplis, Tabea Springstein, Na Yeon Kim |
| SAS | Holly O'Rourke, Cecilia Cheung, Kate Sweeny, Daniel Ozer |
| SPM for fMRI | Halle Dimsdale-Zucker |
| SPSS | Gene Brewer |
| Stan | Kevin Esterling (Political Science) |
| Stata | Kevin Esterling (Political Science) |
Other Resources
- UCR Statistical Consulting Collaboratory (“ask a statistician”): https://collaboratory.ucr.edu/about/policies
- UCR GradQuant: https://gradquant.ucr.edu/
- UCLA OARC stats website: https://stats.oarc.ucla.edu/
- StackOverflow for coding: https://stackoverflow.com/questions
- Quantitude podcast: https://quantitudepod.org/
- Dave Kenny’s website: https://davidakenny.net/index.htm
- QuantFish YouTube channel: https://www.youtube.com/@QuantFish
- Paid workshops: CenterStat, Statistical Horizons, QuantFish
- Online classes: Coursera, Harvard Extension, Bill Revelle (https://personality-project.org/r/psych/)
- R resources: (https://psychmeta.com/learning-R/), Danielle Navarro’s book (https://learningstatisticswithr.com/)
- Matt Diemer’s class on DEI quant methods (https://www.icpsr.umich.edu/summerprog/biblio/2020/shortcourse/Quantitative%20Methods%20to%20Advance%20Diversity,%20Equity,%20and%20Inclusion%20-%20Matt%20Diemer%202020.pdf)